{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 机器学习第一周作业——2012每日单车共享数量预估\n",
    "\n",
    "### ai第八期——高远\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Bikeshare数据集上的特征工程\n",
    "\n",
    "1、\t任务描述\n",
    "请在Capital Bikeshare （美国Washington, D.C.的一个共享单车公司）提供的自行车数据上进行回归分析。训练数据为2011年的数据，要求预测2012年每天的单车共享数量。\n",
    "\n",
    "原始数据集地址：http://archive.ics.uci.edu/ml/datasets/Bike+Sharing+Dataset\n",
    "\n",
    "1)\t文件说明\n",
    "day.csv: 按天计的单车共享次数（作业只需使用该文件）\n",
    "hour.csv: 按小时计的单车共享次数（无需理会）\n",
    "readme：数据说明文件\n",
    "\n",
    "2)\t字段说明\n",
    "Instant记录号\n",
    "Dteday：日期\n",
    "Season：季节（1=春天、2=夏天、3=秋天、4=冬天）\n",
    "yr：年份，(0: 2011, 1:2012)\n",
    "mnth：月份( 1 to 12)\n",
    "hr：小时 (0 to 23)  （只在hour.csv有，作业忽略此字段）\n",
    "holiday：是否是节假日\n",
    "weekday：星期中的哪天，取值为0～6\n",
    "workingday：是否工作日\n",
    "1=工作日 （是否为工作日，1为工作日，0为非周末或节假日\n",
    "weathersit：天气（1：晴天，多云 ",
    "2：雾天，阴天 ",
    "3：小雪，小雨 ",
    "4：大雨，大雪，大雾）\n",
    "temp：气温摄氏度\n",
    "atemp：体感温度\n",
    "hum：湿度\n",
    "windspeed：风速\n",
    "casual：非注册用户个数\n",
    "registered：注册用户个数\n",
    "cnt：给定日期（天）时间（每小时）总租车人数，响应变量y\n",
    "\n",
    "casual、registered和cnt三个特征均为要预测的y，作业里只需对cnt进行预测"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 导入必要的工具包"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 导入必要的工具包\n",
    "# 数据读取及基本处理\n",
    "import numpy as np \n",
    "import pandas as pd \n",
    "\n",
    "#可视化\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "\n",
    "#时间特征处理\n",
    "import time\n",
    "import datetime\n",
    "\n",
    "#模型\n",
    "from sklearn.linear_model import LinearRegression, RidgeCV, LassoCV, ElasticNetCV\n",
    "\n",
    "#模型评估\n",
    "from sklearn.metrics import mean_squared_error\n",
    "from sklearn.metrics import r2_score  #评价回归预测模型的性能\n",
    "\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 读取数据"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "data = pd.read_csv(\"day.csv\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 1) 训练数据和测试数据分割"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "根据yr字段是否为1，分拆出2011年数据作为训练集trainData，21012年数据作为测试集testData"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Int64Index: 365 entries, 0 to 364\n",
      "Data columns (total 16 columns):\n",
      "instant       365 non-null int64\n",
      "dteday        365 non-null object\n",
      "season        365 non-null int64\n",
      "yr            365 non-null int64\n",
      "mnth          365 non-null int64\n",
      "holiday       365 non-null int64\n",
      "weekday       365 non-null int64\n",
      "workingday    365 non-null int64\n",
      "weathersit    365 non-null int64\n",
      "temp          365 non-null float64\n",
      "atemp         365 non-null float64\n",
      "hum           365 non-null float64\n",
      "windspeed     365 non-null float64\n",
      "casual        365 non-null int64\n",
      "registered    365 non-null int64\n",
      "cnt           365 non-null int64\n",
      "dtypes: float64(4), int64(11), object(1)\n",
      "memory usage: 48.5+ KB\n"
     ]
    }
   ],
   "source": [
    "trainData = data[data.loc[:,'yr'] == 0].copy()\n",
    "testData = data[data.loc[:,'yr']==1].copy()\n",
    "\n",
    "trainData.info()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 2) 适当的特征工程（及数据探索）"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "将dteday转换为一年中的第几日特征dayCount，使得string转化为int类型，有效利用数据,然后将dteday删除"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "def getInterval_train(df):\n",
    "    date=df['dteday']\n",
    "    date=time.strptime(date,\"%Y-%m-%d\")\n",
    "    date1=datetime.datetime(2011,1,1)\n",
    "    date=datetime.datetime(date[0],date[1],date[2])\n",
    "    return date-date1\n",
    "\n",
    "Interval=trainData.apply(lambda r : getInterval_train(r),axis=1).dt.days.copy()\n",
    "trainData['dayCount']=Interval\n",
    "trainData = trainData.drop(['dteday','instant','yr'],axis=1)\n",
    "\n",
    "def getInterval_test(df):\n",
    "    date=df['dteday']\n",
    "    date=time.strptime(date,\"%Y-%m-%d\")\n",
    "    date1=datetime.datetime(2012,1,1)\n",
    "    date=datetime.datetime(date[0],date[1],date[2])\n",
    "    return date-date1\n",
    "\n",
    "Interval=testData.apply(lambda r : getInterval_test(r),axis=1).dt.days.copy()\n",
    "testData['dayCount']=Interval\n",
    "testData=testData.drop(['dteday','instant','yr'],axis=1)\n",
    "\n",
    "# mydate = pd.to_numeric(data[\"dteday\"].str.replace('-',''))\n",
    "# year = mydate//10000\n",
    "# month = (mydate-year*10000)//100\n",
    "# date = mydate%100"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 各属性的统计特性"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>season</th>\n",
       "      <th>mnth</th>\n",
       "      <th>holiday</th>\n",
       "      <th>weekday</th>\n",
       "      <th>workingday</th>\n",
       "      <th>weathersit</th>\n",
       "      <th>temp</th>\n",
       "      <th>atemp</th>\n",
       "      <th>hum</th>\n",
       "      <th>windspeed</th>\n",
       "      <th>casual</th>\n",
       "      <th>registered</th>\n",
       "      <th>cnt</th>\n",
       "      <th>dayCount</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>365.000000</td>\n",
       "      <td>365.000000</td>\n",
       "      <td>365.000000</td>\n",
       "      <td>365.000000</td>\n",
       "      <td>365.000000</td>\n",
       "      <td>365.000000</td>\n",
       "      <td>365.000000</td>\n",
       "      <td>365.000000</td>\n",
       "      <td>365.000000</td>\n",
       "      <td>365.000000</td>\n",
       "      <td>365.000000</td>\n",
       "      <td>365.000000</td>\n",
       "      <td>365.000000</td>\n",
       "      <td>365.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>2.498630</td>\n",
       "      <td>6.526027</td>\n",
       "      <td>0.027397</td>\n",
       "      <td>3.008219</td>\n",
       "      <td>0.684932</td>\n",
       "      <td>1.421918</td>\n",
       "      <td>0.486665</td>\n",
       "      <td>0.466835</td>\n",
       "      <td>0.643665</td>\n",
       "      <td>0.191403</td>\n",
       "      <td>677.402740</td>\n",
       "      <td>2728.358904</td>\n",
       "      <td>3405.761644</td>\n",
       "      <td>182.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>1.110946</td>\n",
       "      <td>3.452584</td>\n",
       "      <td>0.163462</td>\n",
       "      <td>2.006155</td>\n",
       "      <td>0.465181</td>\n",
       "      <td>0.571831</td>\n",
       "      <td>0.189596</td>\n",
       "      <td>0.168836</td>\n",
       "      <td>0.148744</td>\n",
       "      <td>0.076890</td>\n",
       "      <td>556.269121</td>\n",
       "      <td>1060.110413</td>\n",
       "      <td>1378.753666</td>\n",
       "      <td>105.510663</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.059130</td>\n",
       "      <td>0.079070</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.022392</td>\n",
       "      <td>9.000000</td>\n",
       "      <td>416.000000</td>\n",
       "      <td>431.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>2.000000</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.325000</td>\n",
       "      <td>0.321954</td>\n",
       "      <td>0.538333</td>\n",
       "      <td>0.135583</td>\n",
       "      <td>222.000000</td>\n",
       "      <td>1730.000000</td>\n",
       "      <td>2132.000000</td>\n",
       "      <td>91.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>3.000000</td>\n",
       "      <td>7.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.479167</td>\n",
       "      <td>0.472846</td>\n",
       "      <td>0.647500</td>\n",
       "      <td>0.186900</td>\n",
       "      <td>614.000000</td>\n",
       "      <td>2915.000000</td>\n",
       "      <td>3740.000000</td>\n",
       "      <td>182.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>3.000000</td>\n",
       "      <td>10.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>0.656667</td>\n",
       "      <td>0.612379</td>\n",
       "      <td>0.742083</td>\n",
       "      <td>0.235075</td>\n",
       "      <td>871.000000</td>\n",
       "      <td>3632.000000</td>\n",
       "      <td>4586.000000</td>\n",
       "      <td>273.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>4.000000</td>\n",
       "      <td>12.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>6.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>0.849167</td>\n",
       "      <td>0.840896</td>\n",
       "      <td>0.972500</td>\n",
       "      <td>0.507463</td>\n",
       "      <td>3065.000000</td>\n",
       "      <td>4614.000000</td>\n",
       "      <td>6043.000000</td>\n",
       "      <td>364.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           season        mnth     holiday     weekday  workingday  weathersit  \\\n",
       "count  365.000000  365.000000  365.000000  365.000000  365.000000  365.000000   \n",
       "mean     2.498630    6.526027    0.027397    3.008219    0.684932    1.421918   \n",
       "std      1.110946    3.452584    0.163462    2.006155    0.465181    0.571831   \n",
       "min      1.000000    1.000000    0.000000    0.000000    0.000000    1.000000   \n",
       "25%      2.000000    4.000000    0.000000    1.000000    0.000000    1.000000   \n",
       "50%      3.000000    7.000000    0.000000    3.000000    1.000000    1.000000   \n",
       "75%      3.000000   10.000000    0.000000    5.000000    1.000000    2.000000   \n",
       "max      4.000000   12.000000    1.000000    6.000000    1.000000    3.000000   \n",
       "\n",
       "             temp       atemp         hum   windspeed       casual  \\\n",
       "count  365.000000  365.000000  365.000000  365.000000   365.000000   \n",
       "mean     0.486665    0.466835    0.643665    0.191403   677.402740   \n",
       "std      0.189596    0.168836    0.148744    0.076890   556.269121   \n",
       "min      0.059130    0.079070    0.000000    0.022392     9.000000   \n",
       "25%      0.325000    0.321954    0.538333    0.135583   222.000000   \n",
       "50%      0.479167    0.472846    0.647500    0.186900   614.000000   \n",
       "75%      0.656667    0.612379    0.742083    0.235075   871.000000   \n",
       "max      0.849167    0.840896    0.972500    0.507463  3065.000000   \n",
       "\n",
       "        registered          cnt    dayCount  \n",
       "count   365.000000   365.000000  365.000000  \n",
       "mean   2728.358904  3405.761644  182.000000  \n",
       "std    1060.110413  1378.753666  105.510663  \n",
       "min     416.000000   431.000000    0.000000  \n",
       "25%    1730.000000  2132.000000   91.000000  \n",
       "50%    2915.000000  3740.000000  182.000000  \n",
       "75%    3632.000000  4586.000000  273.000000  \n",
       "max    4614.000000  6043.000000  364.000000  "
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "trainData.describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 归一化各属性"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th>holiday</th>\n",
       "      <th>weekday</th>\n",
       "      <th>workingday</th>\n",
       "      <th>weathersit</th>\n",
       "      <th>temp</th>\n",
       "      <th>atemp</th>\n",
       "      <th>hum</th>\n",
       "      <th>windspeed</th>\n",
       "      <th>casual</th>\n",
       "      <th>registered</th>\n",
       "      <th>cnt</th>\n",
       "      <th>dayCount</th>\n",
       "      <th>temp_nor</th>\n",
       "      <th>atemp_nor</th>\n",
       "      <th>hum_nor</th>\n",
       "      <th>windspeed_nor</th>\n",
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       "  <tbody>\n",
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       "      <th>0</th>\n",
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       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
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       "      <td>0.363625</td>\n",
       "      <td>0.805833</td>\n",
       "      <td>0.160446</td>\n",
       "      <td>331</td>\n",
       "      <td>654</td>\n",
       "      <td>985</td>\n",
       "      <td>0</td>\n",
       "      <td>0.360789</td>\n",
       "      <td>0.373517</td>\n",
       "      <td>0.828620</td>\n",
       "      <td>0.284606</td>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>0.363478</td>\n",
       "      <td>0.353739</td>\n",
       "      <td>0.696087</td>\n",
       "      <td>0.248539</td>\n",
       "      <td>131</td>\n",
       "      <td>670</td>\n",
       "      <td>801</td>\n",
       "      <td>1</td>\n",
       "      <td>0.385232</td>\n",
       "      <td>0.360541</td>\n",
       "      <td>0.715771</td>\n",
       "      <td>0.466215</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0.196364</td>\n",
       "      <td>0.189405</td>\n",
       "      <td>0.437273</td>\n",
       "      <td>0.248309</td>\n",
       "      <td>120</td>\n",
       "      <td>1229</td>\n",
       "      <td>1349</td>\n",
       "      <td>2</td>\n",
       "      <td>0.173705</td>\n",
       "      <td>0.144830</td>\n",
       "      <td>0.449638</td>\n",
       "      <td>0.465740</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0.200000</td>\n",
       "      <td>0.212122</td>\n",
       "      <td>0.590435</td>\n",
       "      <td>0.160296</td>\n",
       "      <td>108</td>\n",
       "      <td>1454</td>\n",
       "      <td>1562</td>\n",
       "      <td>3</td>\n",
       "      <td>0.178308</td>\n",
       "      <td>0.174649</td>\n",
       "      <td>0.607131</td>\n",
       "      <td>0.284297</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0.226957</td>\n",
       "      <td>0.229270</td>\n",
       "      <td>0.436957</td>\n",
       "      <td>0.186900</td>\n",
       "      <td>82</td>\n",
       "      <td>1518</td>\n",
       "      <td>1600</td>\n",
       "      <td>4</td>\n",
       "      <td>0.212429</td>\n",
       "      <td>0.197158</td>\n",
       "      <td>0.449313</td>\n",
       "      <td>0.339143</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   season  mnth  holiday  weekday  workingday  weathersit      temp     atemp  \\\n",
       "0       1     1        0        6           0           2  0.344167  0.363625   \n",
       "1       1     1        0        0           0           2  0.363478  0.353739   \n",
       "2       1     1        0        1           1           1  0.196364  0.189405   \n",
       "3       1     1        0        2           1           1  0.200000  0.212122   \n",
       "4       1     1        0        3           1           1  0.226957  0.229270   \n",
       "\n",
       "        hum  windspeed  casual  registered   cnt  dayCount  temp_nor  \\\n",
       "0  0.805833   0.160446     331         654   985         0  0.360789   \n",
       "1  0.696087   0.248539     131         670   801         1  0.385232   \n",
       "2  0.437273   0.248309     120        1229  1349         2  0.173705   \n",
       "3  0.590435   0.160296     108        1454  1562         3  0.178308   \n",
       "4  0.436957   0.186900      82        1518  1600         4  0.212429   \n",
       "\n",
       "   atemp_nor   hum_nor  windspeed_nor  \n",
       "0   0.373517  0.828620       0.284606  \n",
       "1   0.360541  0.715771       0.466215  \n",
       "2   0.144830  0.449638       0.465740  \n",
       "3   0.174649  0.607131       0.284297  \n",
       "4   0.197158  0.449313       0.339143  "
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "numerical_features = ['temp','atemp','hum','windspeed']\n",
    "numerical_features_nor = ['temp_nor','atemp_nor','hum_nor','windspeed_nor']\n",
    "    \n",
    "for col in numerical_features:\n",
    "    temp = trainData[col].copy()\n",
    "    temp = (temp-temp.min())/(temp.max()-temp.min())\n",
    "    trainData[col+'_nor'] = temp\n",
    "\n",
    "for col in numerical_features:\n",
    "    temp = testData[col].copy()\n",
    "    temp = (temp-temp.min())/(temp.max()-temp.min())\n",
    "    testData[col+'_nor'] = temp\n",
    "\n",
    "trainData.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 分布以及散点可视化检验归一化效果"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x864 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x864 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x864 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x864 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "myShow = numerical_features\n",
    "for col in myShow:\n",
    "    plt.figure(figsize=(12,12))\n",
    "    plt.subplot(2,2,1)\n",
    "    sns.distplot(trainData[col], bins=30, kde=False)\n",
    "    plt.title(\"Distributing of %s\"%col)\n",
    "    plt.subplot(2,2,2)\n",
    "    plt.scatter(range(trainData.shape[0]), trainData[col].values,color='purple')\n",
    "    plt.title(\"scatter of %s\"%col)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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IVJSUptAoteYlX7bjsqq2ixRSmoSIiIikEpem0Ci15iXnq0aomoTUQjPDIiIi0hbi8o/T5CVvunUTN525ia0f2MpzLnoO07dNMzEyUTHFQqTizLCZXQy8H/gBYBnY5+57zWwN8CFgBDgO/Kq7f6t5QxUREZFuNr5nvKzlcqW85MIFd7k1ORaeWmBpYQnIvhaydKY0M8NngDe4+48CPw38tpldCrwJmHL39cBU+L2IiIhITeLykgEmRibY3be7aLa3dMHd/Kn5lUA4L8tayNKZKs4Mu/s3gG+EXz9lZl8BLgS2AC8Ld9sPfAL4/aaMUkRERDIRV9osq1bMpXnJSZ3vDt94uGzBXZS5E3NMjEy0pI20tL+qFtCZ2QjwYuAB4PvDQBl3/4aZPa/hoxMREZHMxAWes/fPcnT/0Za0Yo6rMHH4xsPMn5pPdxBjpUayUiekVOpg2MzOBf4G2Onu3zFLV7vPzHYAOwCGh4drGaNk7M4HZivuc/Xl+l2KiHSbuMAzX6WhdPvUrqmmB5RxlSRSB8IAJb03shq7dIZU1STMbIAgEJ509wPh5m+a2fPD258PPBb1s+6+z93H3H3sggsuaMSYRUREpAniAs+4Tm5ZtGJudIe7vKhuetKbKgbDFkwBvwf4irv/WcFN9wLbw6+3A/c0fngiIiKSlWoDz2a0Yi5dKDe+Zxya0UjOUNk1AdLNDF8BXAv8gpl9Ifx3JfA24BfN7Bjwi+H3IiIi0qESA8+S7Vm1YgbK0hwawlGVCQHSVZP4FPF/Go37KxAREZGWGt02yoFrDkTf6EGps2ZVZEhqxTy0bqgpaQ1ZpHlI+1MHOhEREVkxtC6mC9y6IXYe38nWO7YCcODaAw3t8JbUinl8zzgDqweKtg+sHmDs+rGimsSl3+fW5hLP2ax8ZOksVZVWExERke6W1AUuqeZvrbPE+frFcakQQ8NDK8euts5x6XgLNTrNQzqXgmERERFZkRR4ToxMxKYy1BIMH7zhINO3TSfmBC+cXuDgDQc5duhY1SkaRfflxBzWb/iSM7ROjTfkLAXDIiIiUqS0C1xeUipDkqjudUDFQBiCesLT75o+e66CRiBpAuS4+yKSp2BYREREUhkajl7IlpR7G5dasSq3quYqEYtPLxYF0knpGlm1kZbOpQV0IiIikkrcQrak3Nu4KhFVdZCLEtNVrlBcuTbVF5ZCCoZFREQkldFto2zet7moYsPmfZsTZ1qzLF9Weq6kcm0ieUqTEBERESBdSkGaHNzC41ifxbZzrpkRmWKRT9dYOX9MbWLVF5ZCCoal5e58YLbiPldfPpzBSEREelejyqaVHqfeQHho3RDrr1xftFhu/ZXrObr/aKryb5HHVH1hKaBgWERERBJTCqoJhqOOU6t8o48ow1cMpy7/Vkj1haWUgmERERFJXTatUipFI1MQko5Vbfk3oKy+sCpNCCgYFhEREdKVTUuTShF3nFrHVMvPRN6PklnmZnTTk86kahIiIiKSqmxamuoMjUpBKMwBnhiZYHffbiZGJiqWRYu6H3C2k13+WHdtv0uVJgRQMCwiIiKUl03Lrc2xKreKA9ceWAlC06RSNGJWNV+yDai6TnD+fuTW5oq25zvZ5Y8Vt7BPlSZ6j4JhERERAYJAcufxnWy9Yytn5s8EjTEKgtDcmlzkz5WmMwytq6Nag8HO4zsZ3TZac53gugJyJ9UMtHQPBcMiIiI9LCoNIbFrnBX/fFR1hriUi7HrxyqOx/psJRBNu6iv1MEbDtbV4a7SDHS1qRvS3rSATkREpEfFLSJLLI3mrDS9KK3OkJf/PqpSw4MffjAxUPUlX1nIlmZRX9R9mr5tOn78KRXOQBfej9Iax1p41/kUDIuIiPSouBlg66/QNc6TawBDfOmzjXs3Vgy484Ho+J7xsn0r1Qme2jUV2Z2uFqUfDuZOzAWBdsnxa6nHLO1DwbCIiEiPiks38CVnYPVAYsBabf3hvNJZ47jAdW52LnGGudr7VKuyxyBhvNKZFAyLiIj0qKSavON7xoMgNKZmcGn94Xt+4x6WFpaAYAb1nt+4ByhOHSgNmLfesTX2HPnjx80wV3ufMMitydWVS1zpvNKZFAz3mDsfmG31EJomzX27+vLhDEbSeGl/b2nuXzc/B3qZmb0C2Av0A+9297eV3D4M7AeeG+7zJnc/lPlApa0kpSHkg9DSvGKAvoE+Fk4vsLtvN0PDQ8yfml8JhPOWFpa47z/ftxL85tbkWHhqoShgvm/HfWzYvqEoB7dwDI26TxiMXTfG8BXDlXOi0whzphsxXmk9VZMQEelwZtYPvBPYCFwKXGVml5bs9ofAh939xcBrgFuzHaW0o9Lawvn6voUzsVH1h82sqOzawumFyOMvfndxpa5vVMC8+PQixw4dqziGeu/T1ju2sunWTcW31Whg9QBj1401bLzSepoZFhHpfC8FHnL3rwGY2QeBLcCXC/Zx4Dnh10PAo5mOUNpWmjSEwn0mRiYammqQzw2OGkPaPOSk8cbdNjEyUXXbaOs3Bb5dSMGwiEjnuxB4pOD7k8DlJfvcAvydmf0X4NnAy7MZmnSbRi8Ui8u1jSv7BvWVMFsJsE/MlaU7JBlYPaBAuEspTUJEpPNZxLbSt/irgPe5+0XAlcAdZlb2HmBmO8xs2symH3/88SYMVdpRNU0kGrlQLC7XdmZyhru231VT97kk+QB7ZUY4bQk2gw3bNygQ7lIKhkVEOt9J4OKC7y+iPA3idcCHAdz908CzgPNLD+Tu+9x9zN3HLrjggiYNV9pJUYDo0d3XCoPlhdML9A/2Fx0j310utza6XXOU3Npc5ExrfjxxdY7rmZmOqqucisORfUfUaa5LKRgWEel8nwPWm9klZjZIsEDu3pJ9ZoFxADP7UYJgWFO/Ett4Iz8DWxosz5+ax92DwLdgAdmmWzcxeO5g6vMOnjsYOdNaKWCtZ2a6nkA63xlPAXH3Uc6wiEiHc/czZvZ64GMEZdNud/cHzezNwLS73wu8AfgrM/tvBBeHf93dG9SnSzpZXICY3x4VnC4vLjN47iBvfOKNqY5Vy3mj1FvCLLYGcUqFneaSFvfVuvBPWkPBsIhIFwhrBh8q2XZTwddfBq7IelzS/mIbb4QzsNUErdUEm3EzvHHHaEQlh/E94xy49kBd7ZrnTszx9vPfXlRRo3BxH9CUhX/SPEqTEBER6WHje8YZWD1Qtn3h9AIzkzOJQWvaY5UxYmd4o44xsHqAV+1/Vd3B5Oi20eRA2IKgO5ERWVouP2tcKe1E2o+CYRERkR6Wb0RRuvht/tQ89+24j/VXro8MTqOC2agGHaWL7fLd4JLqAJeOZ1WucReyYxtuGGy9Yyu+nBAtVyjFNjc7V1P6h7SW0iRERER61MEbDnJk35HYyg2FHeLS5sCWNryoNX/2zPyZla/zgXn++PWITZXwID86KU0j7nFa2acvfp9GlqSTxlIwLCIi0oMO3nCQ6XdNV9wvqUNcGrX8bFKqQSNSJQ5ccyDytrnZObbesbUo5xeCmfAN2zckfnAAYm+rd+GfNJeCYZEIdz4wW3Gfqy8fzmAk1Ukz7qzP1Y6Pk4gEdXPTaMWMZrNTDYbWxS8azAfbhbPZ669cz9H9R2ODXeuz2PSKoXWqJtHulDMsIiLSgypd8gfoH+xvyYxmNYv2ahG3SC9/X0e3jbLz+E5uXr6Zncd3cuzQsdjax2PXj5FUpVCBcPvTzLCIiEgPSpMDO3he0ERjYmQiMee30XV1x/eMR6YqNCowj5r9TRpz0oz0sUPHGFg9wOJ3o4PluFxn1SJuHwqGRUREetBlOy6rmDOcX7iWVDM336GukXV1qw1Waz1H2uMl1U+uVFc5Kte5GY+Z1E5pEiIiIj1o062bGLt+LLGurvVbxZq5zaqrW5qq0MogcXzPeFBWLULFusSUzyyrFnF70cywiIhIj9p06yY23bqpbKYSgrSEuDzZwuCu2+rqRqUvAPQN9LG8sFy2f5rc69Jc5257zDqdZoZFRER6XGmzjKF1Q2e/j1AY3DV7sVuW8h8K5k7MgQfpCwd+7QAHrjkQGQhDuo51pbnO3fSYdQPNDIuIiEhkDu3s/bNM3zZd1KAiv5BtZQb1xFxkZ7Z8O+dOyoGNSl8gOgZe4Uue3JnOy/OA17xwTWSu8ZoXrkk/WGkYBcMiIiJtrhmVByodc2ZyhqP7jxYHeQYbtm8AKE6riAgEG9k1Lis1pSlUaNFcOrs+MznDwx9/OHLfhz/+cMd9gOgGSpMQERFpY1GX7u/bcR8zkzNNPWbkLKkHpcQib4vQaYvCqk5TqBAIl5aDm5mc4a7tdyXOInfS49UtFAyLiIi0sWZUHkhzzKRFXtXMoHbSorCoZhxxcmtzFWeEN+/bXFaCrtKCu056vLqFgmEREZE21ozKA2mOmbTIq5oZ1E5aFFa6kDC3Nkf/YH/xThZ0nXvjE2+MX2C4bqisHFza2fROery6hYJhERGRNhYXHOXW5Bp+zMLt669cX1ZbN3/ZP20nuEZ2jctKYX3jNz7xRrbcvqWoysbWO7ay6dZNQOW2zoXSfHjpxMerG2gBnTTNnQ/MtnoIIiIdb3zPOHe/9m6WF4vLGsyfmuf9L38/Tz70ZNUL6yq1O05aPJc//uEbDzN/aj72HEPruqPFcFKnumo65SV1sctblVNY1gp61EVERNrY6LbR2MDz4amzVQmqaelbKYhLWjyXt3HvxsggvX+wny23b+n4IDittG2doz6A9A30YWYsLSwBnVmBoxsoGBYREWlz80/Gz8AWyi+CSxNIJQVxaXKKo2aIc2tzbNy7UYFchNFto8zeP8uRfUfwJcf6jVXnrGLh9ELRftX8DqUxFAyLiIi0udyaXGJKQqFGVCOIu6RfmmucdlZUzqae5KtJ+JKXBcJ5qiiRLQXDIiIibWxmcoZnvvNM6v3TVCOo1HCjUk5x2uPIWWmrSYAqSmRNwbCIiEgbm9o1VZaXGydNNYKDNxwsarEclWucZmFYvm5uPsCrJme5F6Wd7VVFiewpGBYREWljSUHU2PVjHDt0LPXM7MzkTFEgnBeVp1opBSKpcUevBMPVzIxXrCZhaHa9RRQMi4iItEBSIFV4m/VZZNeyoXVDK/Vu05raNRXbNa3aPNVmNAPpJNXOjK+/cj3T75qOPFa+SYe0hoJhERGRjCUFUkDRbVGBcK2X0pMC1WrzVNMusutW1cyMr9RtjqC0iNar2IHOzG43s8fM7EsF224xs6+b2RfCf1c2d5giIiLdIymQiltoZf220gVt877NNV1Kjw1UjaoDsmq6r3WjambGk36n1fwuZyZnmBiZYHffbiZGJpiZnKlu0BIpzczw+4C/AN5fsv0d7v6/Gj4iERGRLldLioEvOzcv31zXeaOqRGAwdt1Y1cF1Nd3XulE1M+Nxv1df9qoCYS1YbI6KwbC7f9LMRpo/FBERkd5QKZCKXGjlMDEyUVfA2egAtpfrDKctPweNSSnRgsXmqSdn+PVm9mvANPAGd/9Wg8YkIiLS1SoFUmWzt6FGzAb2cgDbSNV8sKgmcI7T6wsWm6nWYPhdwFsI1qS+BfhT4DeidjSzHcAOgOHh4RpP19vufGC21UMQEZEGShNITe2aipxNrGU2UM0xmiPug0XU47153+a6fge9vmCxmWoKht39m/mvzeyvgL9N2HcfsA9gbGwspqCLiIhI94oLRuOCofxtu/t2R5ZCq2Y2ULmm2Yp7vDfv21xX+bRGzC5LtIrVJKKY2fMLvn0V8KW4fUVERHpZPjiaOzEHfjY4SlMJIG7Wr1G5ptJ4jX688xUkDlx7gFW5VeTW5uquKiLF0pRW+2vg08CLzOykmb0OeLuZzZjZF4GfB/5bk8cpIiLSkeoJjhpRvky5ptlq5ONd+kFq/tQ8Z+bPsPWOrew8vlOBcIOkqSZxVcTm9zRhLCIiIl2nnuCoEdUflGuarVoe77g0mrgPUodvPKxAuIHUgU5ERKSJ6g1G663+ENUGuG+gT7mmTRKV29s30MfC6QV29+2ObL0dl9Md94Fp/tQ8M5MzCogbpKacYREREUmnlZ3aZiZn+Py7P19+g5azN83otlE279vM0LohMMitzWFmzJ+aj8wZT0qjSfrApJzvxlF5+jvDAAAgAElEQVQwLCIi0kSlwVGWC5+mdk2xvLhctn35zLKCqSYa3TbKzuM7uXn5ZgbPHWRpYano9sKc8aQ0mqQPTMr5bhylSYiIiDRZqxpdJAVMCqayUSlnPCmNZnTbKIdvPBzMKkfcLo2hmWEREZEOlC+5tbtvNxMjE5Gl2pICptyaXDOHJ6G4xzn/u6mURrNx78ay2wEWTi+kKs8nlSkYFhER6TBpaxeP7xmnbyD6rX7hKQVTzTYzOcMz33mmbHv/YP9KsFspjSZ/e25tcVA9f2o+db1qSaZgWEREpMOkrV08um2UV773lViflR1jaWFJecNNFpezPXjeYFHaTGGOcVT94LgUGzVPaQzlDIuIiFQhriZslirloZaO0Zejy0cob7g+lZ4LsaXRnizPAU46R1zeMARXBaJKtkl6CoZFanTnA7MV97n68uEMRiIiWUmqCZtlEJK06CpqjBiR5dS0CKt2aZ4LtdaYXgmyE353Rbx1z8VuoDQJEZEuYGavMLOvmtlDZvammH1+1cy+bGYPmtmdWY+xG9TTWrmRkhZdRY0xLpjSIqzapXku1FJjuigfHKqqCa20idpoZlhEpMOZWT/wTuAXgZPA58zsXnf/csE+64E/AK5w92+Z2fNaM9rOVk9r5UaKa9MMRM5E5vUN9rG8cDaHNb8Iq/CYkk6a50It7bQjP8w0YFwST8GwiEjneynwkLt/DcDMPghsAb5csM9vAe90928BuPtjmY+yC9TbWrmRSmsXz0zOcNf2uxJ/pjAQzsvPJioYrk7a50K1NabrDWbreS6W5ifn1ubYuHdj1z83lCYhItL5LgQeKfj+ZLit0A8DP2xm95vZZ8zsFZmNrou0srVyJYdvPIwv1dZnWbOJ1WvWc6HeD1a1nn9mcoa7X3t30UK9+VPz3PMb93R9Ko2CYRGRzldeN6s803AVsB54GXAV8G4ze27Zgcx2mNm0mU0//vjjDR9op2tla+VK4qoNpKGFdNVr1nMhKsjO/4UPrRti6we2VhxXLeLKwPVCCT6lSYiIdL6TwMUF318EPBqxz2fcfRF42My+ShAcf65wJ3ffB+wDGBsbq22asY00owxaq1orN43VPpvY65rxXCjKMz4xh/UbvuQMrTv7/I0rtVbamKMavdy6WzPDIiKd73PAejO7xMwGgdcA95bsczfw8wBmdj5B2sTXMh1lxtJ2aesGNd8ng7HrxroruO8Co9tGV2aI86kvhc/fjXs30j/YX/Qz/YP9bNy7seZzJl0d6PYrBwqGRUQ6nLufAV4PfAz4CvBhd3/QzN5sZr8c7vYx4JSZfRn4R+D33P1Ua0acjXYpg5aFau6T9dvKZf2td2xl062bmjgyqVXS83d02yhbbt9SlKKx5fYtdX2oiWvdXdg6ulspTUJEpAu4+yHgUMm2mwq+duB3wn89oV3KoFUjTVpH1D7V3Cdfdm5evrnRQ5cGiyuRNzc717T0H6Anq0koGBYRka7UTmXQ0kjT0Sxun9yaXOoFdO16/7tVLYHrzORMbOe53Jpc07ogdl0+fEpKkxARka7UzmXQosRdFj984+GK+wDlFQiiaLFcpmrNW5/aNRXdec5g6Zmlnkn/yYqCYRER6UrtXAYtb2ZyhomRCXb37Y69LD5/an4leIpLh5h/cr7ovsZydZrLUq1567FpLx600K7qZ5qk8Lk7MTLR0QtTlSYhIiJdq50v+5amPCTJL5pKSv0ovK8TIxPR+61TikSWas1bj/s958usxf1MVtKk9HQSzQyLiIi0QNSsYZx88JQ29aPTUkS6VVyAWilwjfv9JXUYzPJ3222VWhQMi4iItEA1l7XzwVPa1I9OSBHpBfV8KFmVO3vxPrc2d/b3GSG3Npfp77YTK7UkUZqEiIhIC8RdCi+tIlAaPKVN/WjnFJFesiq3amUWNU2psqj0mTPzZ4AguC69bWD1QF3NNmrRaZVaKtHMsIiISAvEzRqOXTemGd0ukA9qC0ve5YPaJJWabbTDjH+3peFoZlhERKQF8gFMo5snSHuoFNTGSWq2Aelm/JvRlKNQtz13FQyLiIi0iFIZulctebVJzTbSpiBkVemhm567SpMQERHpcN1U87Vb1FJJIqnZRtoUhG6r9JAFzQyLiIh0sG6r+dot4ha7JQW1Sc024n6XpSkRldIspJyCYRERkSo1OyezmnMvnF6oKTdVmquWvNrYKg0xJdWiPgglHVuiKU1CRESkCvkAZO7EHPjZmdgsUhOizl1YraCQZgJbq5YPTNVWaUjbuMX6rWMrPWRBwbCIiEgVGp2TWU2+bzVd6zQT2Dq1fmCqtnRa2g88SZ3rRGkSTXXnA7OtHoJIy6X5O7j68uEMRiLSGI3svlVtvm/ac3RyzdduUGtZNaiuSkNSjnDUmGpJm6l2hruVKUS1UjAsIiJShUZ236o0y3z4xsMraRC5tTlya3LRaREF5bjSdDmT5sqqXXHUIr1qx5Qk7sPa7P2zHDt0rCzg7dTFnAqGRUREqlBLlYA4sUHTiTkOXHOgaNv8qXms3+gf7GdpYan4BwqugqfpcibNlVW74qJFehVmiKs598rsbsQxF59eZPq26ZXn3NyJOQ5ce2AlQO7ExZzKGRYREalCI1viVhsc+ZIzeN7gyrmt38r2UU3Z1suyXfHotlF2Ht8ZXB2IUc25i/Kd45SmIDtM3zbdsWXdNDMsIiJSpUZ136rmMnfe/JPzbNy7MXE2sN2Dj27XinbFcbPR1m9VfVirZpFmEQ/OFbVYr90XcyoYFhERaZFqLnPn5dbkKgbQ7R589IKs2xXHpe9Ue9Wing9SvuQMrB5oSApRlpQmISIi0kKj20YZ3zMemfJQqn+wHyAxEO6E4EMar1HpO5U+SCU9T/PnbEQKUZY0MywiIlKjRpSRyudoVqoFm68SceDaA7H7DK3rjFJW0hyNmI2ulLrjS87As8PZ34KnbP5DWNYz4o2gYFhERKQGjSojFZejaf3Gq/a/quxYcSkVQ+uGgoVUIjUo/GCXW5NjVW5VbHfDxe8uMnb9WGR5tU6kYFhERLpSs4v/19JYIWpMcTmavuyRx2lkaTcRKP9gN39qnoHVA+TWxtS1Bo7uP9oRKRBpKGdYRES6Tq3tcKtRbWOFuDHl1uQi94/L3WxkaTcRiP9gB5SViCu8vVtK+GlmWEREuk497XDTiusGFxfExo1pVW5V2Qp8DNZfuT723J2YlyntK+4D3PyT82y9Y2tZA5hKP9dpNDMsIiJdp9ntcGcmZ3jmO8+Ube8f7I9NV4gNOE7Nc9HPXFTcNMGDy9CNnMmW7jUzOcPEyAS7+3YzMTJR9fMm7gPc0PAQo9tGg6sQVfxcWvWOu1E0Mywd4c4HZls9hKbp5vsm0irNboc7tWuK5cXlsu2D5w3GztjGjQng4Y8/XNbVqxPa2ErrNWIhZ6U89GbkqUeNO9/WedOtm2o+bi00MywiIl2n2e1wky4rVzOmFTFV1brlMrQ0T1z6zX3/+b7Ux6iUh96oPPXCmeC7tt9VXkUlbOuc9QyxZoZFRKTrNLsdbi0zz/lzx+Vfxp1HJEncB6bF7y5y8IaDqWdZK+Wh15unXjoTHFtX28n8ioiCYRER6RrNLqe2cvwTc0GOb0TTgSSj20bjWy/XcDyRpPSbI/uONCTloBF/V3H1tKNkfUVEwbCIiHSFRjXBSHt8nJUAtlLnt9KGBv2D/SwtLJ3dITyO9Ru+5FV1kmv2BwBpb+N7xmOvNlTqaphGo/6uqglws74iomBYRES6QrPLqUXObHnlzm9RDQ36BvrONjQomBH2JS9qa1tJsz8ASHZq/VAzum2Uu37tLny5PPC1fiv6vvRDGQR57knnq/bvKu5+JM1gFyq8IpLVBz0toBMRka5QSxOMaso61VquLSqYWF5cZvDcwWBBUkwViTSSAhXpHPU2ibnsP18WvX3H2e2l55g/NR98GKtwvmqe90n3I25R69j1Y5EL87JonJOnmWEREekK1Sxqq2VGtdZybbUE0WkvKTe7nrJko96rGvm84CP7juBLjvUbl+24rChfuFLObtz5qnneJ92P/NWTtDO9WTTOyVMwLCIiXaGaWqi1vNHWWmu1UjBRTz3kZtdTlmw04kPNpls3xS6Wm5mcSZWiELVPNc/7SvejmooUWX7Qq5gmYWa3m9ljZvalgm1rzOzvzexY+P/3NXxkIiIiVYiqhbph+wamdk2VpULU8kZba63VpJrH9dZDbnY9ZclGUge4euWvgqRilKUhVPO8b+T9aOZjUirNzPD7gL8A3l+w7U3AlLu/zczeFH7/+w0fnYiISBUKZ56SUiFqnVGtpdZqmprHtS4SanY9ZclGMzq85VVT0iyuxm/a530j70czH5NSFYNhd/+kmY2UbN4CvCz8ej/wCRQMi4hIG0lKhcjyjRbKg9b8Ard8kFFP8Frvz0vrNfNDTbVpBfWkITTyfmT5Qa/WnOHvd/dvALj7N8zseQ0ck4iISN2SUiHSvNE2sqyTSqBJJc36UJO2pFnh/vVo5P3I6oNe0xfQmdkOYAfA8PBws0+XmTsfmG31EKQD6HmSTprH6erLu+f1Q7JRKRUi6Y02Kng9cM0BDt94mI17Nzak+1azVsaLFIq6ClJp/1pV8wGynZrF1BoMf9PMnh/OCj8feCxuR3ffB+wDGBsbq78VioiISArVpkIUvjlbn0V275o/Nd/Q7lsqgSaFmhEgRl0FWTi9ENQYLpFbm8vk6ke7XSmptenGvcD28OvtwD2NGY6IiEhjVLMKvrTAf1Ib22qbWsxMzmB9FnmbSqBJXjObTIxuG2Xn8Z3cvHwzO4/vZOPejWVVSArHUYtqGsC0W7OYijPDZvbXBIvlzjezk8DNwNuAD5vZ64BZ4FeaOUgREUlmZq8A9gL9wLvd/W0x+70a+AjwU+4+neEQWyJtzmFVK+5JP6ObD3CigmuVQJNCzU6lKZ113rB9Aw9++MGiGeI0Vz7iZq+rufrRbldK0lSTuCrmJv0Fi4i0ATPrB94J/CJwEvicmd3r7l8u2e884L8CD2Q/yvZW7Ztw2hnduCDb+i1VjWLpHc0MEKPSEo7uP8qqXHkYmBSAv//l7+fhqYfPjq3KcoX5QLq0BfkKh4mRiczzh2tNkxARkfbxUuAhd/+auy8AHyQogVnqLcDbge9lObhOUE26QjUzunGBjC+7AmEp0swmE3GzzlF5wxD9vD14w8GiQLjwOPlyhUkNYIrSQBI0Mj0kLQXDIiKd70LgkYLvT4bbVpjZi4GL3f1vsxxYp6jYUrnKrnMrP5dhFy3pbM3sJtiIKx9H9h1JPH6lHP1qUpGyzh9uemk1ERFpuqjVWSsXIs2sD3gH8OsVD1RnOcx2KpcUJ26Mh288HDlTNrRuiJ3Hd6783IFrD6zMhKVpxZxlcw/pXM1sMhGXwpBbm+PM/JlUz8+kRaVpyhVm2fyjWgqGRUQ630ng4oLvLwIeLfj+PODHgU+YGcAPAPea2S+XLqKrpxxmu5VLipI0xo17N8YGrrXeN7VLlmo0q8lE3IeyjXs3Aumen9YfXW4wf/xK4gLyuONmefVEwbCISOf7HLDezC4Bvg68Brg6f6O7zwHn5783s08Av9voahKd0FgiaYw7j+9c2ac0MJgYmaj5vqldsrRapQ9laZ6fl+24jOl3lb9kXDJ+SaqfjwvIN2zfwNH9R1t69UTBsIhIh3P3M2b2euBjBKXVbnf3B83szcC0u9+bxTjarVxSlEpjjAtcO+G+SWdrdopRpY6Llc696dZNQJA77EuO9RuX7bhsZXua80N0QD58xXBLr54oGBYR6QLufgg4VLLtpph9X9aMMaQprdRqtY6xE+6bdK5WphhVc+5Nt25KHfxGiQvIW331RNUkRESkIZq5Gr5Rah1jJ9w36Vyt7MjWbt3gWkEzw1KTOx+YbfUQRKTNdMJisVrHmPRznVBBQ9pb1mk4hc/ZuAYYvZQCpGBYREQaolOCwtLANj8DVstCuFovb3fKYyXZyDINp/Q5mzSmXqFgWERE6tYJZdXyGjnWWipodNJjJdloZj3q0g9eC6cXKgbCfQN9LJxeYHff7p74sKacYRERqVsn5R02cqy1XN5Oe/6ZyRkmRibY3bebiZGJTNvTSrYqdW+rVVELZA8+eMW1YAbAgkYcZhbs561pj5w1zQyLiEjdOqn0WOxYT8wxMTJR1SxYLZe3o/YvHZdmj3tPMyoqVNMCOd9pcWJkoixgbrd64Y2mmWEREalbXPDXjnmHlQLVNLNg+VnbuRNzZc2wky5vz0zORDfPLhlXJ820S3uamZyJ/eBVqvA5W+sH206+kqFgWERE6tZJpceixlqoMOiMeoMvuvQMwWr8MMCtdHl7atdU9Op9K25p20kz7dJ+8s/ROLm1udiUjLgPi9ZnsQFuVDpGJ6VWKE1CRETq1gll1fKKxpqQshCVqnDgmgNYn+HLJRGtn73MnCQ2mPXi9Ac1+ZB6JKVH9A0E86Bxf6dRi/kAfMnLUnVWFudFPFdrTa1oRaUVBcMiItIQre4iVY38WFdSHUoMDQ/FBhRlgXAozaxtbJC7rjjIbWZ1Ael+Sc/FlcVxnJ3Bnb1/lmOHjq0EoBu2b1hpu1yoMMBNU6Kt2isZB284yPRt0ytXT7LKlVeahIiI9Kyk9I5q38jTzNqmTSdpVnUB6Q1Jz8WlhaWi7xefXmT6tumiFIej+4+WBcJ5+b+LNIvzqrmSMTM5UxQIF46v2bnymhkWEZGuUXjZ1voNX3KG1sVfak1K7zh84+HkMlQF0s7aVpNO0kkz7dJe4lIdYkUEoPm/n1L5ALfSh8XSv4lK6Q+x+fQpzlUvBcMiItIVSi/b5t/IK11qjess98x3nkl13qRgOy4AUJArzZR/ft21/a7YGd5KfMkZWD0Qm6oTl/IDwQK9jXs3FuUWVyoVmBTwNjtXXmkSIiLSFZIu21Z7qXVq1xTLi8sV98svmosLhDt5hb10ttFto7H57UXiSv2FqTlxqTpJVVnOzJ8p+j5NqcCkgHfh9EJT/240Myw95c4HZls9BBFpkkqXUqu51Jp231o7zWlmWLIQN3tr/UFFlKHhIdZfuZ6j+49GzgAnXcUY3TbK7P2zTL9ruuy20ud5mlKBSakd86fmm7qQTjPDIiLSFSpdSq3mUmvafRMbeKhWsLRY3ILNV+1/FTcv38zO4zvZdOummhdrHjt0LPa2wud5mqY8RYtGIzRzIZ1mhkVEpCskzSz1DfSxcHqB3X27U9UuTbMAKW7RXD5POG4xkGoFS1bSLtisNY89bZ5vpVKBpbn1tZyvHgqGRUSkK5Q208ivhs+tzbHw1EJZbdXCn0k8VvgGvf7K9UW1WKOCikq1V1UrWLLWzAWbSYvoCp/nSUF51OK6pPM1g4JhERHpGlFv/BMjE2Ul0hafXuSu7Xet/EypWrtgVaq9umH7BuULS9cY3zPO3a+9u2yxad+q8izcuKA8Tb1iaO4HSeUMi4hIS81MzjAxMsHuvt1MjEw0fNV43KXVfHvZ0vMdvOEgB649UFMViEqXcZNyLEU6zei2Uc55zjll25fPLKfO702T+mD91tSmMwqGRUSkZbIoP5Z0abV0UU69XbAqXcbV4jnpNvNPRjemmTsxl+pDbprUB192tWMWEZHulKb+aJRqZpOT6qFCcYBabxes8T3jsXVbQYvnpPvEPqeNVB9yK/19Jp6jQRQMi4hIy9RSfqyW2eRVufglMoVvtLV0wSoMzKd2TXHJL1wSuV//YL8Wz0nXiQxmjdRXV8pKqpV8mMxi0amCYRERaZk09UdLVTObnA+cSxfQFSrsbpU0yxVXRq00MD/56ZOMXT9Gbm1uZb/c2hxbbt+ixXPSdYqC2bBOcezVlTB1ovSD6+i2UXYe38nNfjNb79haU83jeqiahIiItEyl+qNRqplNTrNSvbC7VWR9YYOx68ZSr4RffHqRY4eO8cYn3ph4XpFuUVopYmJkIrZEWv5Kzuz9s5GlCptZCi6OgmEREWmZtE0BCsXVNo2a1U27YC0/s7zz+M6qxqMuc9Ktai0vCJWb1iw+vVi0UHXuxBx3v/ZuDt94mPkn56s+X70UDIuISEtVOxMUN3u7/sr1ZfsmNQUolQ9gqxlPNYG5SKeIaoRRqVFNodFto8zePxtZmWVFyfblxeWqGuM0knKGRUSko4xuG2XD9g3FC20cju4/WpaLGLu4J0ItAWzU8fNpHs2unyzSLLVWeSl07NCx+EA4hWrPVw/NDIuISMeJeqMtfPMsvLy7YfuGotzE9Veu5+j+o2Vv9vmFdNXMREW1gF58epHDNx5m4akFlhaWgOxnukTqUW/6z8zkTPIVmYhqE/Wcr14KhkVEpOPEvlmHQWfh5d2j+4+WrUgfvmI4yE8sqDIxf2q+przFwkvCvuQrxyqVD9YVDEu7qyf9J59iEcf6jct2XBb5gbSW8zWC0iRERKSl0qYTFO5nfdG5DvmZ2UJRl1tHt40yeO5g2c+v5C1W0Q0vrmtdFC2sk06QlP5TSVIFl4HVA7xq/6vYdOumonJsubU5+gf7azpfIygYFhGRlknbQKN0v/wMbKGB1QOR2yE6CE0TmKbJW0zqWldKC+ukE0TVDk5b7zfp72rzvs1AUHrtwLUHANh6x1be+MQb2XL7lszrC+cpTUJERFomaaFO4Rth3GyT9Ru+7CspDfnc3VJRQWjaShOVgua0s71ZznSJQH3l0Wqt9xubYhF2mEuqUtGqFCLNDIuISMukXagTt58vOzcv38zO4zsZ3TZa1eXdyEoTESrN5qaZ7c16pkuklrbljZD0N9iIKhXNoGBYRERaJm075rT7VXN5N7+v9cfUWiPdbG6loDq3NrcSrItkpVWBZ9LfYNoPv1mXJVSahIiItEzadszVtG2u5nJrfr+oblm5tTk27t2YqpoEwIFrDkTePv9keWUJkWZrZXfEuL/BNFUq6m34UQvNDIuISMukncmtZ0FPLWPY+oFgUU81QXU+J7KUFs1JK6S9mpKlNGlMrZjR1sywiIi0VNqZ3GYusGnEsauZvRZptnZ5PpYu4tuwfQMPfvjBlVrcq3LFoWgrZrQVDIuIiDRAUTe6GlbvizRSOzwfo1IePv/uz2N2Nk9//tR8URpEPQ0/aqVgWEREMldPyadG/HyztLI8lEipVj8fo1IelheXy/YrLKfYihltBcMiIpKpmckZ7n7t3StvinMn5rj7tXcD6RbItGKBjYhUr5rUhvy+rZjRVjAsIiINlzRze/jGw2WzQ8uLyxy+8XCqN7y0jTpEpLXSNrbJ75uX9Yy2qkmIiEhDVSr2n184Uyq/vVKN0VaWjBKR9KKqR/QN9NE/2F+0rdULTRUMi4hIQ9VTGilN16ykhTRvP//tsUF01oX8RXrd6LZRNmzfsNLYxvqNl/zmS9hy+5amlEmslYJhEZEuYGavMLOvmtlDZvamiNt/x8y+bGZfNLMpM1vXrLFUmrnNrc1F3p5bm4sNpA/feHjl+9iObx7OLkcE0a1qTSvSy2YmZzi6/yi+5AD4knN0/1EAdh7fWdRKvZUUDIuIdDgz6wfeCWwELgWuMrNLS3b7J2DM3X8C+Cjw9maNp1Kx/417N5ZdJs2Lyy+cPzXPbgtmdIGKbZSheDa6Va1pRXpZp/zdKRgWEel8LwUecvevufsC8EFgS+EO7v6P7v50+O1ngIuaNZhKXaZGt42y5fYtZTPE86fmITm+Xak8cfjGwyuzTYn7h7PRyjMWyV6n/N0pGBYR6XwXAo8UfH8y3BbndcDhqBvMbIeZTZvZ9OOPP17TYNK0Th7dNsrguYPlP1w5vmV5cTl2EV6p/Gx0O7amFel2nfJ3p9JqIiKdL2o+NTKsNLNrgDHg30fd7u77gH0AY2NjKULTaGlKIzV7dqhwNrpdWtOK9JJO+burKxg2s+PAU8AScMbdxxoxKBERqcpJ4OKC7y8CHi3dycxeDuwC/r27P9PsQVXqEhdXgzS3NseZ+TNluYaV5NMu5p+cLztfO7SmFek1nfJ314iZ4Z939ycacBwREanN54D1ZnYJ8HXgNcDVhTuY2YuBvwRe4e6PNXMwM5MzHL7xcFEqQ1SXuLhZo417NwKUHSPJ0Lohdh7fmbhPq1vTivSiTvi7U86wiEiHc/czwOuBjwFfAT7s7g+a2ZvN7JfD3f4EOBf4iJl9wczubcZYZiZnuOc37okMYktLpCXlFsfmFEeo97Kr6g+L9LZ6Z4Yd+Dszc+Avw1yzIma2A9gBMDw8XOfpREQkirsfAg6VbLup4OuXZzGOwzceZmlhKfb2+VPzzEzOFKUvxM0aJbVxHVo31JDLrvn6w/nZ6agZbBHpbvXODF/h7i8hqG3522b2c6U7uPs+dx9z97ELLrigztOJiEg7S5PWkLYTXSVb79had8H+TqmDKiLNU1cw7O6Phv8/BtxFUOtSREQkVpoqEpWC0bkTcxy49gAHbzgI1J7q0Cl1UEWkeWpOkzCzZwN97v5U+PUvAW9u2MhERKTj5NbmKs4Op6kxmioYdZi+bRqAo/uP1pTqEFfRot3qoIpI89QzM/z9wKfM7CjwWeCgu//vxgxLREQ60ca9G+kbiH9rSbvYLXUw6nBk35FUqQ5Rs8eVuuWJSPerORgO235uCP/9mLvvaeTARESk84xuG+WV733lSoWI3NpcUP83phNdnKggNU5cW+bC2eX8Qrm5E3PgxbPHlbrliUh3Uwc6ERFpqLR1RQubcuTWlDfM2Lxvc3B7QlUJAOu3yIC4cHY5aaFcvYvwRKSzKRgWEZFMlAa/C08trJRhi2rQsXnfZnYe38nEyERsQDyweoAN2zcU5QzntxemOmihnIjEUdMNERFpunwzjnyawvyp+cR6xIU5v0kB6+Z9m9l066aKqQ5xOchaKCcimhkWEZGmq9SMI0o+CI6t+LBuKFXzDohv/ayFciKimWEREWmafAWHNKy0e6IAAA8TSURBVM04SuVnbRtR8SGp9bOI9DbNDIuISFOUtjquRmGwmw9Y8/nGtbZgTruwT0R6i4JhERFpiqgKDnEGnj3AqmetKqomURi4KpAVkWZRMFzizgdmWz0EEYnQqL/Nqy8fbshxpLJqKjWsPn81O4/vbOJoRESiKWdYRESaoppKDSpxJiKtomBYRESaopoucipxJiKtomBYRESaIl/BIbc2l7ifSpyJSCspGBYRkaYZ3TbK4LmDsbc3osRZvnzb7r7dTIxMMDM5U/OxRKT3aAGdiIg0VWw+sFH3ornS8m35Vs6Aqk+ISCqaGRYRkabKrYlOk2hEnnBU+bbCVs4iIpUoGBYRkaaZmZzhme88U7a9f7C/IXnCcbPOqk4hImkpGBYRkaaZ2jXF8uJy2fbB8wYbksYQN+sct11EpJSCYRERaZq4Gdr5J+czHomISDQFwyIi0jRxecGNqiscF1Qr2BaRtBQMi4hI00Q13mhkXeFmB9si0v0UDIuISNPkG28MrRsCa0xd4ULNDrZFpPupzrCIiDTV6LbRptX8zR93atcUc7NzDA0PMb5nXDWGRSQ1BcMiItLRmhlsi0j3U5qEiIiIiPQsBcMiIiIi0rMUDIuIiIhIz1IwLCIiIiI9SwvoRESkrcxMzqg6hIhkRsGwiIi0jYM3HGT6tmnw4Pu5E3Pct+M+AAXEItIUSpMQEZG2MDM5UxQI5y0+vcjUrqnWDEpEup6CYRERaQtTu6bKAuG8udm5bAcjIj1DwbCIiLSFpIB3aHgow5GISC9RMCwiIm0hNuA1GN8znu1gRKRnKBgWEZG2ML5nnIHVA8UbDcauG9PiORFpmq6pJnHnA7MV97n68uEMRiIiIrXIB7wqqyYiWeqaYFhERDrf6LZRBb8ikimlSYiIiIhIz1IwLCIiIiI9S8GwiIiIiPQsBcMiIiIi0rMUDIuIdAEze4WZfdXMHjKzN0Xcfo6ZfSi8/QEzG8l+lMlmJmeYGJlgd99uJkYmmJmcafWQRKQHKBgWEelwZtYPvBPYCFwKXGVml5bs9jrgW+7+QuAdwB9nO8pkM5Mz3LfjPuZOzIHD3Ik57ttxnwJiEWk6BcMiIp3vpcBD7v41d18APghsKdlnC7A//PqjwLiZWYZjTDS1a4rFpxeLti0+vcjUrqkWjUhEeoWCYRGRznch8EjB9yfDbZH7uPsZYA5YW3ogM9thZtNmNv344483abjl5mbnqtouItIoCoZFRDpf1Ayv17AP7r7P3cfcfeyCCy5oyODSGBoeqmq7iEijKBgWEel8J4GLC76/CHg0bh8zWwUMAU9mMroUxveMM7B6oGjbwOoBxveMt2hEItIrFAyLiHS+zwHrzewSMxsEXgPcW7LPvcD28OtXAx9397KZ4VYZ3TbK5n2bGVo3BAZD64bYvG+zWjOLSNOtavUA0rjzgdm2Oo6ISDtx9zNm9nrgY0A/cLu7P2hmbwam3f1e4D3AHWb2EMGM8GtaN+Joo9tGFfyKSOY6IhgWEZFk7n4IOFSy7aaCr78H/ErW4xIRaXdKkxARERGRnqVgWERERER6loJhEREREelZCoZFREREpGcpGBYRERGRnqVgWERERER6loJhEREREelZdQXDZvYKM/uqmT1kZm9q1KBERERERLJQczBsZv3AO4GNwKXAVWZ2aaMGJiIiIiLSbPXMDL8UeMjdv+buC8AHgS2NGZaIiIiISPPV0475QuCRgu9PApeX7mRmO4Ad4benzeyrNZzrfOCJGn6uE+i+da5uvn9de9+21X7f1jV6LO3uyJEjT5jZiRp+tF2fPxpXdTSu6mhc1cliXKlet+sJhi1im5dtcN8H7KvjPJjZtLuP1XOMdqX71rm6+f7pvgmAu19Qy8+162OscVVH46qOxlWddhpXPWkSJ4GLC76/CHi0vuGIiIiIiGSnnmD4c8B6M7vEzAaB1wD3NmZYIiIiIiLNV3OahLufMbPXAx8D+oHb3f3Bho2sWF1pFm1O961zdfP9032TerTrY6xxVUfjqo7GVZ22GZe5l6X5ioiIiIj0BHWgExEREZGepWBYRERERHpWWwXDldo7m9k5Zvah8PYHzGwk+1HWJsV9+x0z+7KZfdHMpsysY2qapm3LbWavNjM3s7YopZJGmvtmZr8a/u4eNLM7sx5jPVI8L4fN7B/N7J/C5+aVrRhnLczsdjN7zMy+FHO7mdmfh/f9i2b2kqzH2I3Svh5kNJbjZjZjZl8ws+lw2xoz+3szOxb+/30ZjKPsuRg3jiyflzHjusXMvh4+Zl8o/Js3sz8Ix/VVM/sPTRrTxeFrzlfC19Qbw+0tfbwSxtXqx+tZZvZZMzsajmt3uP2SME46ZkHcNBhuzySOShjX+8zs4YLH6yfD7a19PXb3tvhHsAjvX4EXAIPAUeDSkn1uAG4Lv34N8KFWj7uB9+3ngdXh19d3030L9zsP+CTwGWCs1eNu4O9tPfBPwPeF3z+v1eNu8P3bB1wffn0pcLzV467i/v0c8BLgSzG3XwkcJqiZ/tPAA60ec6f/S/t6kOF4jgPnl2x7O/Cm8Os3AX+cwTjKnotx48jyeRkzrluA343Y99Lw93kOcEn4e+5vwpieD7wk/Po84F/Cc7f08UoYV6sfLwPODb8eAB4IH4cPA68Jt99W8DqeSRyVMK73Aa+O2L+lr8ftNDOcpr3zFmB/+PVHgXEzi2r+0W4q3jd3/0d3fzr89jMEdZs7Qdq23G8heDH7XpaDq1Oa+/ZbwDvd/VsA7v5YxmOsR5r758Bzwq+H6KBa4u7+SeDJhF22AO/3wGeA55rZ87MZXddK+3rQSoXvI/uBVzb7hDHPxbhxZPa8TPE3UmgL8EF3f8bdHwYeIvh9N3pM33D3z4dfPwV8haDjbUsfr4Rxxcnq8XJ3Px1+OxD+c+AXCOIkKH+8mh5HJYwrTktfj9spGI5q71z6RFvZx93PAHPA2kxGV580963Q6wg+IXWCivfNzF4MXOzuf5vlwBogze/th4EfNrP7zewzZvaKzEZXvzT37xbgGjM7CRwC/ks2Q8tEtX+XUlm7PaYO/J2ZHTGzHeG273f3b0AQ4ADPa9HY4sbRDo/h68NL1bcXpJFkPq7wEv6LCWYV2+bxKhkXtPjxMrN+M/sC8Bjw9wSz0N8O46TSc2cWR5WOy93zj9ee8PF6h5mdUzquiDE3XTsFw2naO6dqAd2GUo/bzK4BxoA/aeqIGifxvplZH/AO4A2Zjahx0vzeVhGkSrwMuAp4t5k9t8njapQ09+8q4H3ufhHBZaw7wt9pN+jU15N21m6P6RXu/hJgI/DbZvZzLRxLWq1+DN8F/BDwk8A3gD8Nt2c6LjM7F/gbYKe7fydp14htWY6r5Y+Xuy+5+08SXFF+KfCjCedu2bjM7MeBPwB+BPgpYA3w+1mPK0o7vamlae+8so+ZrSK4bJv2Ek8rpWpdbWYvB3YBv+zuz2Q0tnpVum/nAT8OfMLMjhPkAt1rnbGILu1z8h53XwwvhX2VIDjuBGnu3+sIcs9w908DzwLOz2R0zaeW8o3XVo+puz8a/v8YcBdBoPDN/OXX8P9WpTbFjaOlj6G7fzMMYpaBv+Lspf3MxmVmAwQB56S7Hwg3t/zxihpXOzxeee7+beATBO+zzw3jpNJzZx5HFYzrFWG6iYcxzntp4eNVqJ2C4TTtne8Ftodfvxr4uLt3wkxOxfsWphL8JUEg3El5p4n3zd3n3P18dx9x9xGCfOhfdvfp1gy3Kmmek3cTLH7EzM4nSJv4WqajrF2a+zcLjAOY2Y8SBMOPZzrK5rkX+LVwFfNPA3P5y7BSszTPqUyY2bPN7Lz818AvAV+i+H1kO3BPK8aXMI6WPi9L8jRfRfCY5cf1mrAawSUEH/o/24TzG/Ae4Cvu/mcFN7X08YobVxs8Xhfkr0aaWQ54OUE+8z8SxElQ/ng1PY6KGdc/F3ygMYI85sLHq3Wvx9Wstmv2P4LLsP9CkO+yK9z2ZoLgCYI34o8QJKJ/FnhBq8fcwPv2D8A3gS+E/+5t9Zgbdd9K9v0EHVJNIuXvzYA/A74MzBCu3u2Ufynu36XA/QSror8A/FKrx1zFfftrgsuWiwSzDq8DrgOuK/jdvTO87zOd9Lxs539Rz6kWjeMF4fP2KPBgwfN7LTAFHAv/X5PBWKKei5HjyPJ5GTOuO8LzfpEgQHl+wf67wnF9FdjYpDH9LMHl8S8WvB9e2erHK2FcrX68foKgotEXCQLLmwqe/58liJc+ApwTbs8kjkoY18fDx+tLwAc4W3Gipa/HascsIiIiIj2rndIkREREREQypWBYRERERHqWgmERERER6VkKhkVERESkZykYlkyZ2XPN7IZWj0NEREQEFAxL9p4LdFwwbGb9rR6DiIiINJ6CYcna24AfMrMvmNmfmNnvmdnnwj7luyHo+25m/2xm7zazL5nZpJm93MzuN7NjZvbScL9bzOwOM/t4uP234k5qZi8zs0+Y2UfDY0+GRb8xs3Ez+yczmwl7y58Tbj9uZjeZ2aeAX2n+QyMiIiJZUzAsWXsT8K8e9Cv/e4KuPC8l6Ot+mZn9XLjfC4G9BIW7fwS4mqDo+e8C/73geD8BbAJ+BrjJzH4w4dwvBnYSNJJ4AXCFmT0LeB/wn9x9FFgFXF/wM99z95919w/WfI9FRESkbSkYllb6pfDfPwGfJwh614e3PezuMx70e38QmPKgQ8wMMFJwjHvcfd7dnyBoP/lS4n3W3U+Gx/xCeJwXhef6l3Cf/cDPFfzMh+q4fyIiItLmVrV6ANLTDHiru/9l0UazEeCZgk3LBd8vU/y8LW2hmNRSsfCYS+FxrMIYv1vhdhEREelgmhmWrD0FnBd+/THgN8zsXAAzu9DMnlfl8baY2bPMbC3wMuBzVf78PwMjZvbC8Ptrgf9T5TFERESkQ2lmWDLl7qfChXBfAg4DdwKfDteynQauIZi1TeuzwEFgGHiLuz9a5Xi+Z2avBT5iZqsIgunbqjmG/P/t2qERgEAMRcGkIDTtUQBd0CIGFQSOBo4ju/JU5JubDwDzymeGCfPJzC0izqraR98CAMzJTAIAgLb8DPMrmblExPF6vqpqHXEPAPBtYhgAgLbMJAAAaEsMAwDQlhgGAKAtMQwAQFtiGACAtsQwAABt3achnKylBEgdAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 864x864 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x864 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x864 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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ycrLIpyQiyoSIxJnpry3wO5uIWpnp9zbTJIiIiIioY0UGw/ZsNN8Wkb0ico+IbLWX3yAiD4nI3fa/s/NvLhERERFRdkzSJJ4B8BpVfcqeqvebIjJu3/dnqvr5/JpHRERERJSfyGBYrdprTp3SHvsf67ERERERUcszyhkWkW4RuRvAYwC+oqp77Lu2icj3ReSjIuI7B7qIbBCRSRGZPHz4cEbNJiIiIiJKzygYVtVZVT0bwBkAzhGRlwB4L4BfA/AKAEsBvCfgsdtVdUhVh5Yv76iqRERERERUcbGqSajqT2FNq3u+qj6qlmcAfArAOTm0j4iIiIgoNybVJJaLyMn27RqA1wL4oYicai8TABcC+EGeDSUiIiIiyppJNYlTAewQkW5YwfMtqvpFEfk3EVkOQADcDeDtObaTiIiIiChzJtUkvg/gpT7LX5NLi4iIiIiICsIZ6IiIiIioYzEYJiJqcSJyvYg8JiK+YzfE8g8i8oBdDvNlRbeRiKiqGAwTEbW+GwCcH3L/KgAD9r8NAD5eQJsqoT5ax0j/CLZ2bcVI/wjqo/Wym0REFWMygI4okZv2HDRa75Jz+3JuCVF7U9U7RKQ/ZJULAHzanlH0ThE5WUROVdVHC2lgSeqjdezasAszT88AAKYOTGHXhl0AgMF1g2U2jYgqhD3DRETt73QAD7v+PmQva2sTmyfmA2HHzNMzmNg8UVKLiKiKGAwTEbU/8VmmviuKbBCRSRGZPHz4cM7NytfUwalYy4moMzEYJiJqf4cAnOn6+wwAj/itqKrbVXVIVYeWL19eSOPy0tvXG2s5EXUmBsNERO3vNgD/y64q8UoAU+2eLwwAw9uG0bOkp2lZz5IeDG8bLqlFRFRFHEBHRNTiROSzAF4N4BQROQRgC4AeAFDVTwDYDWA1gAcAPA3g8nJaWixnkNzE5glMHZxCb18vhrcNc/AcETVhMExE1OJU9eKI+xXA/y6oOZUyuG6QwS8RhWKaBBERERF1LAbDRERERNSxGAwTERERUcdiMExEREREHYvBMBERERF1LAbDRERERNSxGAwTERERUcdiMExEREREHYvBMBERERF1LM5A1wJu2nPQaL1Lzu3LuSVERERE7YU9w0RERETUsRgMExEREVHHYjBMRERERB2LwTARERERdSwGw0RERETUsRgMExEREVHHYjBMRERERB2LwTARERERdSwGw0RERETUsRgMExEREVHHYjBMRERERB2LwTARERERdSwGw0RERETUsSKDYRF5loh8W0T2isg9IrLVXv4CEdkjIvtE5HMisjj/5hIRERERZcekZ/gZAK9R1ZUAzgZwvoi8EsCHAXxUVQcAPAHgrfk1k4iIiIgoe5HBsFqesv/ssf8pgNcA+Ly9fAeAC3NpIRERERFRThaZrCQi3QDuAvDLAK4D8CMAP1XVY/YqhwCcHvDYDQA2AEBfX1/a9radm/YcLLsJC1SxTURERER5MBpAp6qzqno2gDMAnAPgxX6rBTx2u6oOqerQ8uXLk7eUiIiIiChjsapJqOpPAXwNwCsBnCwiTs/yGQAeybZpRERERET5MqkmsVxETrZv1wC8FsB9AL4K4E32ausB3JpXI4mIiIiI8mCSM3wqgB123nAXgFtU9Ysici+Am0XkrwB8D8Anc2wnEREREVHmIoNhVf0+gJf6LH8QVv4wEREREVFL4gx0RERERNSxGAwTERERUcdiMExEREREHYvBMBERERF1LAbDRERERNSxGAwTERERUccyqTNMRERERBVUH61jYvMEpg5OobevF8PbhjG4brDsZrUUBsNERERELag+WseuDbsw8/QMAGDqwBR2bdgFAAyIY2CaBBERtY36aB0j/SPY2rUVI/0jqI/Wy24SUW4mNk/MB8KOmadnMLF5oqQWtSb2DBMRUVtgLxl1mqmDU7GWkz/2DBMRUVtgLxl1mt6+3ljLyR+DYSIiagvsJaNOM7xtGD1LepqW9SzpwfC24ZJa1JoYDBMRtQEROV9E7heRB0Tkap/7+0TkqyLyPRH5voisLqOdeWIvGXWawXWDWLN9DXpX9AIC9K7oxZrta5gWFBNzhomIWpyIdAO4DsDrABwC8B0RuU1V73Wt9ucAblHVj4vIWQB2A+gvvLE5Gt423JQzDLCXjNrf4LpBBr8psWeYiKj1nQPgAVV9UFWnAdwM4ALPOgrg2fbtXgCPFNi+QrCXjIiSYM8wEVHrOx3Aw66/DwE417PONQC+LCJ/BOCXALzWb0MisgHABgDo6+vLvKF5Yy8ZEcXFnmEiotYnPsvU8/fFAG5Q1TMArAZwo4gs+A1Q1e2qOqSqQ8uXL8+hqURE1cJgmIio9R0CcKbr7zOwMA3irQBuAQBV/Q8AzwJwSiGtIyKqMAbDRESt7zsABkTkBSKyGMBFAG7zrHMQwDAAiMiLYQXDhwttJRFRBTFnuI3ctOdg5DqXnNt6OYBEFE5Vj4nIlQC+BKAbwPWqeo+IfADApKreBuDdAP5JRP4YVgrFW1TVm0pBRNRxGAwTEbUBVd0Nq1yae9n7XbfvBXBe0e0iIqo6pkkQERERUcdiMExEREREHYvBMBERERF1LAbDRERERNSxOICOiIgoZ/XROiY2T2Dq4BR6+3oxvG2YM+URVQSDYSIiohzVR+u49YpbMTs9CwCYOjCFW6+4FQAYEBNVANMkiIiIcjS+cXw+EHbMTs9ifON4SS0iIjcGw0RERDlqHGnEWk5ExWIwTEREREQdi8EwERFRjmrLarGWE1GxGAwTERHlaNW1q9DV0/xz29XThVXXriqpRWSqPlrHSP8ItnZtxUj/COqj9bKbRDmIDIZF5EwR+aqI3Cci94jIRnv5NSLyYxG52/63Ov/mEhERtZbBdYO48FMXondFLyBA74peXPipC1lJouLqo3Xs2rALUwemALWqgOzasIsBcRsyKa12DMC7VfW7InISgLtE5Cv2fR9V1b/Nr3lEREStb3DdIIPfFjOxeQIzT880LZt5egYTmyf4WraZyGBYVR8F8Kh9+0kRuQ/A6Xk3jIiIiKgsUwenYi2n1hUrZ1hE+gG8FMAee9GVIvJ9EbleRJ4T8JgNIjIpIpOHDx9O1VgiIqIqYC5p++vt6421nFqXcTAsIicC+BcAm1T1ZwA+DuBFAM6G1XP8d36PU9XtqjqkqkPLly/PoMlERETlYS5pZxjeNoyeJT1Ny3qW9GB423BJLaK8GAXDItIDKxAeVdUxAFDVn6jqrKrOAfgnAOfk10wiIqJqCMslpfYxuG4Qa7avaRr4uGb7GuYLt6HInGEREQCfBHCfqv69a/mpdj4xALwRwA/yaSIREVF1MJe0c3DgY2cwqSZxHoDLANRF5G572fsAXCwiZwNQAPsB/GEuLSQiopZWH61jYvMEpg5OobevF8PbhjMLMPLcdpDevl4rRcJnORG1HpNqEt8EID537c6+OURE1E6c/FonrcDJrwWQOmjNc9thhrcNNz0vwFxSolbGGeiIiCg3eebXlpW7y1xSovZikiZBRESUSJ75tWXm7jKXlKh9sGeYiIhyk2etVtaBJaIssGe4w9y052DZTSCiDmKaX5tkIBxzd4koCwyGiYgoN05AGxboJh0IZ7Jtok5WRrWVVsRgmIiIchWVXxs2EC7qh5u5u0T+yqq20oqYM0xERKUqeiBcfbSOkf4RbO3aipH+EU6jTG2JMyWaYzBMRESlKnIgnNNbNnVgCtDjvWUMiKndcKZEcwyGiYioVMPbhtGzpKdpWV4D4aJ6y1qt17jV2ttuqnz8WW3FHHOGiYioVEUOhAvrLauP1rHz8p2Ym5mzlh2Yws7Ldza1MU9xBzsxJ7RcVT/+rLZijsEwERGVrqiBcL19vVaKhM/y8Y3j84GwY25mDuMbx3NvW5LAKs3AQ0qv6sef1VbMMRim0pnUPr7k3L4CWkJE7S6st2zs0jHfxzSONHJvV5LAijmh5WqF489qK2aYM0xERB1jcN0g1mxfg94VvYAAvSt6sWb7mtIDhiSBFXNCy9Vpx7/K+dFpsWeYiIg6SlBvWW1ZzbcXuLaslnubwtI3gjAntFyddPyrnh+dFnuGiYiIAKy6dhW6F3c3Lete3I1V167K/bmTVNSoai93p+ik49/uNYvZM0xERIRyBxwlfW7mhJarU45/K+RHp8FgmIiIyFZmcJP0ueOWZCOKK0kaTythmgQREVHFBQ1e4ox6VIQiJ8YpA3uGiYiIShDVozt//4EpQACotdw9eKnqtW6pPbR7zWIGw0RERAWLGp3vvd8JhB1OwNvuuZxUHe2cH800CSIiooJFjc73u99r6sAUakv9y761Sy4nUREYDBMRERUsqkfXtGf3mZ89s6AcXDvlchIVgcEwERFRwaJmLzPt2Z2bmcPikxZ3RK1borwwZ5iIiKhgUbOX+d0fpHG0gasevyq3thK1O/YMExG1ARE5X0TuF5EHROTqgHXeLCL3isg9InJT0W2k46JmL/O7P2haaOYHU1pBpfs6BXuGiYhanIh0A7gOwOsAHALwHRG5TVXvda0zAOC9AM5T1SdE5LnltJYcUaPzvfff/s7bMfmJyabKEswPprSiKpt0AvYMExG1vnMAPKCqD6rqNICbAVzgWedtAK5T1ScAQFUfK7iNlEJ9tI69O/Y2l1gTYOX6lR0TsFA+oiqbdAL2DBMRtb7TATzs+vsQgHM96/wKAIjItwB0A7hGVf+fd0MisgHABgDo6+vLpbFlCJvgohWmM/YttabAvt37ymkQtQ3WqmYwTETUDsRnmWeaBiwCMADg1QDOAPANEXmJqv606UGq2wFsB4ChoSHvNlpS2GVgAC1xiZgBC+Wlt6/XmuXQQ7oE9dF6pT4HeWGaBBFR6zsE4EzX32cAeMRnnVtVdUZVHwJwP6zguDBlDdIJuwzcKpeIo0qxlaFTBl21+34ObxtGz5KeBct1VjF26Rg+cspH2m6fvRgMExG1vu8AGBCRF4jIYgAXAbjNs85OAL8LACJyCqy0iQeLaqDTOzt1YArQ4z2wRfzIhvWqVq3HNSjw8gtYyhw8V+brWaRO2E+ncol0+11gAhpHGm23z14MhomIWpyqHgNwJYAvAbgPwC2qeo+IfEBE3mCv9iUAR0TkXgBfBfBnqnqkqDYG9cCObxzP/bnDelWr1OMaFnhFlWIrWqv0qKfVKfs5uG4QOhecFdWO++zGnGEiojagqrsB7PYse7/rtgL4E/tf4YJ6WhtHGrnnJUZNcBF2X5HCAi+nzFpV8jer1qOel07ZTyA4d9jRjvvsiOwZFpEzReSrInKfXah9o718qYh8RUT22f8/J//mEhFRKwrrac27xymsV7VKPa6tFHhVqUc9T52yn0Bw7rCjHffZYdIzfAzAu1X1uyJyEoC7ROQrAN4CYEJVP2TPdnQ1gPfk11QiImpVw9uGMXbpmO99RQR7Yb2qVelxDeqZiwpCyigNF9Xb3i46ZT+B49VTxjeOo3Gk0XRfu+6zI7JnWFUfVdXv2refhJWPdjqsgu477NV2ALgwr0YSEVFrG1w3GGs64XYfwe8nySC5sgZ4ValHPU+dsp+OwXWDuOrxq7D2M2tL2+cyPvtipZEZrizSD+AOAC8BcFBVT3bd94SqLkiV8BRwf/mBAwdSNrm93LTnYNlNaAmXnNs+xf+pNYnIXao6VHY7ijQ0NKSTk5OZbc9b7xewgj3vD63pemHPU/VJNILEbftI/4h/b/KKXmzav6nQtlA6PN7pP/tept/bxgPoROREAP8CYJOq/kzEvwSHVzsWcCciovicH7OoH/yogWRhwibY8D62isFH3JSNvPKM4xxHSo/H25Lms5+GUTAsIj2wAuFRVXWSvn4iIqeq6qMicioAznNPREShTIK9NAGe6Y9pFsFHFYLppHnGUcoKSjoVj7elrEGkJtUkBMAnAdynqn/vuus2AOvt2+sB3Jp984iIqNOkGcFv+mOatn5sVSZjyGsyjlaqbNEOeLwtZVXvMJl04zwAlwF4jYjcbf9bDeBDAF4nIvsAvM7+m4iIKJU0AZ7pj2na4KMqkzHkNcCrk0qKVQGPt6WsmRYj0yRU9ZsAghKE27fOBhERlcI0t9iPaSmstOkFVerJy6M0XFklxaoUzEtTAAAgAElEQVSQelKGuMc7j+NUhWOf5rOfBmegIyKiykka4Jn+mKYN9vLK1a2KMoKSTh5EFud453GcqnTsy6j7Hau0WlpZl+lpByytZoal1ahsLK3WftL0hGVdAoryLRPXTvI4Tu167DMvrUZERFS2LC/lpumBKutyblJVuAQepQqpJ516nKpw7MvEYJiIiFpClS7lOs/ZCnmaVTtuQcpOPenk41T2sS+bSTUJIiKi0lWlgkNWiirP1irHraxKAo5OPk5lH/uyp19nzzAREbWEdruUW9REC61y3MpOPcnyOOXZ45/mOAW1K+k2s9jPKvTIMxgmIqKWUNal3LwCm6KC1DyPW9bHpoxKAo6sjlMRwV2S4xTVrrjbzGo/qzD7HtMkiIioJZRxKTfPVIaiJlrI67hVZRa+rGR1nKqabpF1u5Jszy8dogpXLhgMExFRbrLMBcxrtrUweQY2RQX3eR23qgZ9SWV1nKoQ3MV5/qTtCtzegSnfz3zQyVNtac13O0UO3mOaBBER5SLry8VJLsmnvYyfZ2BTZI5sHukHVQ360sjiOFW1MkPW7QraHgTzy92f+aCTp0W1RehZ0lP4bIduDIZzxAk1iKiTZZkLmCSwThuM10frkC6Bzi6cnCpJABE1eKnVxA2uWqGGbxbKmso6Stbt8tseBIDn4+J85oNOkhpHG1h749pS3xsMhomIKBdZ9hyaBtbugMsvkDUNxp1A2i8QThJAVGHEfNbiBFftuP9Byq6KUVS7/Lbn21MMhN7f29db+kkhg2EiIspFlpdlTQJrb8DlF8iGbcvNL/gGAOkW4zzSrALzqooTXFWhYkCR8gzu0vSwZ9kuv3ZMbJ4I/MwPrB7A5McXTu8+sHogk/akwWCYiIhykeVlWZPAOiiADXtMkKCAWefUOBDOKjCvMtPgqh3zi8tQlR72oHasXL8Se3fs9f3MBw2s3Ld7XyFtDsNqEkRElIssqxiYVF4wCaxMg/G0Zc+yDMzbQVFl5NpdVSp4BLVj3+59gZ/5Kp8QsWeYiIhyk9VlWZNL8kG9x9It0DmNdUk5ba92loF5WbIc8FbVQWVBqjrYryoBZVg7gj7zVa2yATAYJiKiFhEVWPuObgfwrJOfhVXXrsLgusH5usd+QY43AFq5fiX27d6XKCCKE5hXMfDK+nJ8VQeV+alKKoKfqgSUSdpR5RMiBsNERNQWnEBlfOM4Gkca88sbRxrYtWEXDn7rYFM+ozvIAbAgANq7Y2+qtA6/H37v9qoaeOUx4K3sigFR5k9KfIK8qgz2q0pAmaQdVT4hYjBMRESZqY/Wm4LR2rLafK9sEQbXDWJi80RTMAxYwcxd2+8KrOjg3Pa7L8+e0KpWWajK5fiieE9K/JS9706wPvP0jHWFYVbRu6KcgDJpYFvVEyIGw0RElIn6aB07L9+JuZm5+WWNIw3cesWtAMwnukjbcxRYCSJBRYc0AZDJD39Vg86qXI4HisnfNRnwWGZuq191EqcntqzgsqqBbRKsJkFERJmY2DzRFAg7ZqdnjUa7Oz/4UwemAD2eMlAfrcdqR1DQIt0SuH6aagdOHvLWrq0Y6R+J1d6qVlkwqd5RhKzeE1GiTj7Kzm0NuoIwvnE88XuvLGk+L3lhMExERJlI28OaVdmooEDu5RteHhjgJQ3+0gZrQc87sHqg1IAhy7J4aRRVSizs5KOsfXcLnMr4SCP3E4UsFXVyExfTJIiIKBNh07GmmegibspAWD5j33l9oZfc416OT5vz69fWgdUDgQP98qo+EbTNsgLAsMFsQPZpJKYDHssS9tlyq0K+ORD8fqpqjjyDYSIiysTwtuEFOcMA0L2423iii6zyVIMCubAAL0nwl0UA733ekf6R0N7QrKtP5FXRImnQbjKYLes0kipXOgCCywb6KTvfPOz9FPV5KavMIINhIiLKhF9pszjVJKpSNiqOPAaahQUMefSs5bHNNAF21GC2LN8TVazx7McvWJ9+anpB1RSg/HzzsPdT2OelzDKDDIaJiCgzaS6tV713zs/wtmHcesWtmJ2enV9m2hMeJCxgyKP6RB7bTBNghz1vlqXEqlrjOYj3s+XXg16Fk8ew99PaG9cGtrnMFAoOoCMiosoYXDeITfs3YcvcFmzav6nUoMR01Luqhv4dV9hgvtrSmu9jgpaHcfYPAc3Nq3c7SmCFjRW9mb4nwio0tIKqDHL0CnovSpdVzSWozWWWGWTPMLWEm/YcjFznknP7CmgJEXWCsF5D4HjvtXTJgvrFczNzGN84nk0P+YEpSLfM95DNPjMb8WgzUXm5aXsY06SPFJUuE1ahoT5aLz2oNFG1Wr/10Tqe+dkzvvfprGLXhl1Ys30NNu3ftOD+Mmtbs2eYiIjaUpp6pmG9hu7SUEETeTgBVVKD6wbne4id55g6MIXpp6b9n+/owtzRMFF5uYtq6frKokrVhb02RfV4hgVZWZduK0MZ9XyDao07wsrilVnbmj3DRETUdtLmg4b1Gpoau3QME5snFuS4mg7aMpkVzVFbWsNI/4hxrnXUpefGkUaq/Nmw/G+T1yarHs+wYz28bRhjl475Pq7sigxplZUPbXLcgtYpc8wAg2EiImo7cQbj+AVMpnVdo/jVCPYLUg5+6yD27d7X1AbTgKyrpwvTTx6vLGAS+JjsX9rBS0EBbdBr84X1X8DYZWOZ1k4OCwgH1w02VT5xK7siQ1plDUYzeV+FHduy0j6YJkFERLkr+pJt4GCcA1NNzx00I9bA6gHfS7a1ZfEHqrkvDQcFKZOfmFzQhsDBcstqTSkEJzz7hKZqFt7n9ON3SdpPHj2kQdvUWc10VjKT2etWXbuqEtNOmzL9HGU1GC3u5zbqfVXVYxvZMywi1wN4PYDHVPUl9rJrALwNwGF7tfep6u68GklERK0r70u2cXt23c8dFDDt270Pa7avWbBd5/Gm6QsOJwgJDEY8qcczT89gUW0Repb0LBhI5q3bvLVra+hz+vFekvYbCAik6yENSlFI0ysdpy5wWEDo3k5taQ2LaovQONootZxf1L6ZDurs7etFbWktdY93ks+t933lnNAFHduq1Hk2SZO4AcDHAHzas/yjqvq3mbeIiIjaSp6XbIN+sFeuX9k0pXHQc4f1ILurOTh/D28bPh4kx0ijcIKQOOkXjSMN1JbV5vchaAKTpKPw3Zeks65ZGxZImc6m5n1t4gZnQceltrTWtJ3GkQZ6lvRg7Y1rS51+OmrfwgZ1Hmsca3psV08Xuhd3N10xiPt6mn5u/QJav2oRSfa5qGA5Mk1CVe8AcDTzZyYioo6QZ/3QqJ7dqDYFBoyC+UDKXc3B+bHetH+TlaoQ8Fiv6aemUR+t+19G9lnfWe7u3TvWOOa7Whaj8LOu4BAVSLmfS7r9D4D3tTFJe3ALOi7O40y3UwSTfQsb1Ol97NzMHBaftDjV62nyuQ1KMzJJcYna5zTbjitNzvCVIvJ9EbleRJ4TtJKIbBCRSRGZPHz4cNBqLeemPQcj/xERFUVEzheR+0XkARG5OmS9N4mIishQUW0LnEQhg0FKYT/Yg+sGAwNW57kHVg8sDEYFgRNRuH+sg4KtobcPLcgtdldn8AadQ28f8g+QfVIn/AK2rALZLCc8iQqk3M/1xh1vjAzm66P1wB71sOoEfsclqAxdmRUkTALPuJ+XxtFGqtfT5HMb9wTFLWqf02w7rqTVJD4O4C9hfVT/EsDfAbjCb0VV3Q5gOwAMDQ2lm5aHiIgWEJFuANcBeB2AQwC+IyK3qeq9nvVOAvAuAHuKbF+ekyhEpQiEPXd9tI69O/Y2B50hgbDDHdAB/qWg9u3etyBn0/kh9wtM+s7ra9pOksAv71JkccRJ3YgqqeX0EIY9VxC/4xKU4lJmBQmT4xX0Xl5UW5RLRQyTz23amQbD9rnIGekSBcOq+hPntoj8E4AvZtYiIiKK6xwAD6jqgwAgIjcDuADAvZ71/hLARwD8aZGNy7N+aNQPdthzj/SPLMxbVeuyfdBkGkBzkOENtpzR92mD2aBt5BmwZTnQMe4JUFgwH1ZvOclJVVYnZ1nms5q0Kei9DCwc1Bl3f8L2JWwf85xpsMgZ6RIFwyJyqqo+av/5RgA/yK5JREQU0+kAHnb9fQjAue4VROSlAM5U1S+KSGAwLCIbAGwAgL6+7KY4z6t+qMkPdtBzh5X48lZxcIQFGVFTHAPmP+RFTUnsluVAxyxPgMJ6ApPmNS+qLQodmJimskPWk5R41ws7aUhyrE3qMQdJ8z6N2uciPwMmpdU+C+DVAE4RkUMAtgB4tYicDeti0n4Af5h5y4iIyJTfCKT5rk0R6QLwUQBvidpQGaltaXvYkgbagT1PK6w2uKtJ6Kyid0UvBlYPYGLzhO/kEOMbx0MD4Tg/5GXMxpX1ZWnvPji5nnH2oT5aDy77tqI39vHwO2FpHGlgfOP4fNvSVHbIY5KSvB+bZF+yKk0X1u4iPwORwbCqXuyz+JOZt4SIiJI6BOBM199nAHjE9fdJAF4C4GsiAgDPB3CbiLxBVScLa6WPsqaNBcJ7nvx+pP3aOnbpGMY3juPX3/zroVM1OwF2EUF+HO6gJijolC5BfbRuFBjFnXY5qm27NuzybVPSHsKglAv3AEeT4DBuGkyUMuvtxj0J8r6ueZamK2pGOs5AR0TU+r4DYEBEXiAiiwFcBOA2505VnVLVU1S1X1X7AdwJoPRAGCh2xLhX3CoMYYHU5CeCD2Xvit7U1Rny4C1dFZQnrbMaWNIqrPxV2tc26HhLt4S+TmGzpoUFq07booLD+mg9sBxeknxWv2M4dtkYtkoxszXGrfZS5mc2LwyGiYhanKoeA3AlgC8BuA/ALap6j4h8QETeUG7rwmV5aT7JlM9Oia+1N64FAIxdNhb42NDJMkISSqo4/SwQPjDNKyjYCQuM0r62gTndcxoaCIfVpo0KVp2eWT/O8onNE/6vtyR7rX1fB3v7edbWdcStU11klYeiJC2tRkREFaKquwHs9ix7f8C6ry6iTSayGjGe5pK86UxYJmXXvGrLapXpEfZeio8zgx7gH+yEBUZpX9skjw8Kzr+w/gsYu2wMtaW1BTOzebcdNXArbErtrAcIOu3PYrbGIHFzc4us8lAU9gwTEVFpspg9DUh36dbksYG9gW6eS+c9S3qw6tpVkc9fBL8e06BL/dJlNiNc0DJnedLXtqk8nc8x9U7G4b4aEBTg66wCaqW0BAXC7nzxsPSZwH0OmpEwgkkQmXevq3sSFGfwaNAVlqw+s1XCnmEiIipNViPG01y6NXls1HZ6lvRg5fqV2Ld7XymDoKKEXYpfQLCg9zQo2IkahOg8t+kxWVDtQTHfI+8dhOjXox+n976rpwsnPPsE3yoIYQO3si755bc9ryRXSpJ8pkyukpRR6SRvDIaJiKjlmVy6DQoQTB4bllYQVimizCoBbnF6FnVWsfjkxVh84uLIdkcFRnGrAQQF7c4gRJN1TQPiuZk5LD5xMa56/Crj9gHZB4NN2/MJ6JNMoJE0Zci0zFpRVR6KwmCYiIhKUR+tY3zjeFNJsqSl1aJ668ICBJOevqB1oqoalFU2zitujnDjaMM4SMwyMIrTwx+Wu2saEKepoZzla+jeXtoTqDQ1kNtxcJwJBsNERFS4sNnakgwYiuqtCwsQnB7HqFnsotbxympihix6l4OC+UW1Rb71kcsaDBVncFbQulHTaUdtN66se//TBtppAtp2HBxngsEwEREVLqqsV5KeqLAgIipAMAlA4gYpWfSyZdW7HBTMAyh82ucwcfJxg9Y1LReXxX5WqfffkSagLWMacKD8dCIGw0REVLioS/ZxeqJMfkjL6PHK4jnT9C77HRdv3q37ecrOawbi9cAHrTufexsiauIOU1GvTxlBnknKkLtNA6sHmgZ+Fj0Q1Hdmx8vGMHbpWKKZG5NgMExERJkLCwKiavb69USlnfLXd8S+WOuP9I/k8oObRS9b0t7lOD2WJj3eRQZ1cXrgg9aNqs4QNnFHHGGvT1m9xmEnFH5tmvz48dkTpw5MYe+OvZmcKJgymXQEyPeYMRimtnHTnoOR61xybl8BLSHqbFFBQFjN3tqyGlZdu6rphy9se3FGvzvre0fs5/WDm0XVgaDe5drSWujjsspXBrJNBSgiqHa25x2c6ZbmioB7H6TLPz+5t68309cgrqCTBJNZB71tzPs1K3vSEYDBMBERZSwqCAj78fOrYJDVlL9OgOA3OYPJD65JUBAnNcHE8LZh7Lx8J+Zm5pqWTz85jdvfeXvg5ewsqwJkORAwLKiOunxveryddY41jvm2I00OrHcf/AJhZ/tjl435bqPMygxxp8IuonfbpNJJ3seMM9AREVGmogKxuDN4RU3567utkJ6/JIGi3wxuuzbsapqdK2id2995e9Msad4ZvcIMrhvECc8+YcHy2elZTH5iMrA9SY5LkKwC67Cg2u/YTX48eP+A8NckqAc0ba5w2Ha9s9Vl+RpkJc5U2EC6mR1N+c1oF9SevDAYJiKiTEUFAXGnc816yt8kQYrplM1+64QFrSYaR/0v9XtTTdztGd42jK6e5p/4rp6uRD2iWQV1YUF1nMv3jiRXDNLmCodtd8vcFmzav2l++1Wcttgk8HS3sYi6w03TXwORU3DngcEwERFlKioIaPrx8/Smxd1e3G2ZtM9PqimbQ4JWE3GCTncbRJqjCu/fprIK6sKC6riX7723m9Y5kOyKgYk423Xem7Vlx/O7F9XMslPro/XEVxPC+H1eht4xFPj5Kap3e3DdIDbt34QtugVrb1wb6/OcBeYMExFRpkwGjsWtGBC2vbj1f5MMbEs7ZbNXnJ61oEoYfoMQa0trvjnRgJVakWQgUlbTD4dV1zAphwYYHm8BBlYPYO+OvZnXy01SIcSdu9w40ojMuTXN0zUd2JYmj72MusNlTPXMYJiIiDKX53S1ZWwv6ZTNQUFrnJ41v2DUL9jr6unC9JPTgRUUgHKnH44KqqPKofkd77HLxhYeXwXuueUerNm+JvMqCHFPDJIMPjR5TJyAOc0AuKxOhKqOwTAREVVC2bNQhTHt7Z5f58DU8WmBPQFxkp41v2C077y+pvZMPxUeCAPFDd4Kei2DguqggD+smsTgukGMXepfscE5DmkqeQSJc2Jgkl7jPVZBPeTux5gG2VlUAsmrp7ZKn3cGw0REVLoqTmvrZRIU+PZyKuYD4ixn1PK2Z2vX1tD1ixq8dfs7b8fkJyZj13FOEnT1rggOHouo5xslKr3G731vcjXBdGBbEQPgkkj6HskLg2EiIsqNae9PmRMUZC1oRq3eFb259FQ6wnoV85rW1q82sDvIcWRVx3nBuiF5xqb523mKSq8JnH0t4mqC6VTfaaYEz6vntj5aT/weyQuDYSIiykWc3t6q9mAlUda+BAVeeY3G953a1yfIcZjUcTZ5r3jXDSTWumUEV+5Asra0hkW1RWgcbRhPjuKcPAUFomFBtve5uxd3Y3Z6dsF6Ue33ez0Ofutg5EQoUcJmoCzr885gmIiIchGntzdND1bVlLUvRQ92CuzVDJC0jrO3/SY1iZ22eB9fRJ6qN5BsHGmgZ0kP1t641vx9H3EVIei1BrDgubt6ulBbVvMNxoOE1cxOm9oQFvCW9XlnMExERLmI00NaRgmnvKTZl7TBWlFlqeqj9XhpCILUdZyj1vV9/IHmgWpF5KUHBZLjG8cXPE+a94rfaz3SP7Lguedm5rD4xMW+U50HiVszO87xCyuJV9bnnZNuEBFRLpJMUGBabD+vSQmyELYvYe02mfK5Cpx2BvLO7SHA0NuHIus4my6P03so3ccbU8TUwkBwINk40ljwWiaZNCbJc8dNP0g60YsJ31nwDN4jeWLPMBERZcI9qClJWTHTXs1WrTwR1e60gwiLKlUVlqbQs6QHK9evjJVXWh+tY/qpad9t+b1XfOs5B9DZ42++pIFi3OMaNpDR77XMsjc/qxSdvGpmA9WsXcxgmIiIUvMGevNBSEBZsbAAIyr4aNXKE1HtDpteOEqRJwhhwWPcXs2gwXC1ZTWsunaVcU3ioBrLvSuiZ6wLC+aSHNfhbcOB9Y/LGkSZpK41ED3RS9JUpjJmmQvDYJiIiFILHdTkKSsWFmAAiAw+WrXyRFS7w3Ipo6oiFHmCEDboC7DyVk17/ILeN4tPXByrJrFvUG1Py+xIEigmOa6D6wYxvnHcPzhvoUGUJhO9ZNmjW+YkHAyGPW7ac7DsJlCOTF/fS87ty7klRO0lKhA1nT3Lue13n/PD2KqVJ6LaHTa9cFRQW1QKAADfWsI9S3owsHogdi9qVic2g+sGcfBbB5vbpcDeHXvRd15fU2AXZ3/jtC+LkmZZyLPXNc/Z6MpMfeIAOiIiSi0qEDWdPcsk+PAbgNMKlSei2j24bjBx/dWwAWhBg/aSDNirj9axd8fe5nYK5vOE4w5QizNwLsq+3fsCqx04BtcNYtP+TdgytwWb9m+KDLRM2+c9lo0jDagqastqAKyBfE5bqjYgsgqKGtwYhMEwERGl5jtC3OY3e5af3r5eo+Aj6xH4RTFptzvH1S0qOAwKtJ3eWr+AN0kAMr5x3Le2sDNgzk9YID+wemBB9YmkJzZhz5+0+ojpiZffsZybmZtf38mhr2qFkLKVnfrENAkiIkqt6RK0q5qE3zTAUbmbJnmdVRuAYyqq3UkHQAWlAITVvPXLaQWCA5D6aD30MXHTV8J6mZO8tkHPX1taS3wJ3jS1Iqycmpc77SfPKY+rVK0hStmpTwyGiYgoE6YBql/g7AQIw9uGsWb7mpb6IU8iKFhJMwDK7/iPXeZf1SAoqAWCA5CodIe4gXzQDHb7du9LFMwFPT8QnYfu5vfcYbPBOfsfZxISp7c6jzzZsvNvkyh70p3IYFhErgfwegCPqepL7GVLAXwOQD+A/QDerKpP5NdMIiJqJ86Pst+P9prta5oqT0xsnsDYZWNtExhHBStF1J0NEhaAhF2ydr8ufkGsX4AZVkouSTAX9PxBJwRBg+CSPHdQMLeotiiwqkReFUBasfRg2bWHTXqGbwDwMQCfdi27GsCEqn5IRK62/35P9s0jIqJ2FfWj3Yo9XCaKDFbiTFABhNcJDkxDsAeJuUuqrb1xbVPdaL/Xsba05hsoOlcK3EyPj9+JhHMFwm9/vEH69FPTiZ47KJgDgtN+4gbppoFi2fm3SZWZ+hQ5gE5V7wBw1LP4AgA77Ns7AFyYcbuIiKjNRf1ohwWNVZ6OOUqRwYrfoD0nePXqXdEb2fvpN43u889+fmhViqDXEYDv4DT3rHFuSY9PnMGFUXnUYe87p1LF2hvXArBSVCY2T2Dl+pW+gyaTVqqYOjCFsUvH8JFTPuL7vs+yQkeYOJ/Bqn9ek+YMP09VHwUAVX1URJ4btKKIbACwAQD6+sqt3coawmTK5L3CWsRE6UQNmsn6MnpVFD1YyGSCirD0CHev5IJgWIGH/u2hwJJmYTPrNY42sPbGtb6D/rI8PnEGFwZxepF3Xr5zvkrE1IEp7Lx8Z9Nz+PWC792x17fH3TRPNqidjSMN3/d9Efm3ca7atMIVntwH0KnqdgDbAWBoaCiggiIREXWaqB/toKAxzWX0pLIcnV/2YKE4+ZneQGbm5z7BY0Rt5LDgP+jSeNbHJ87gQi/nucc3js8Hwo65mTmMbxxvOqam7820lSqCth03dztqEGFtqXUloXG0EVmlxG8/WyGHOWkw/BMROdXuFT4VwGNZNoqIiNpfVDAQFDQG9ebllROZdc9WkYOFwqpWmDxfnN5TL/fMenGC2yyOj0nQZzK40F0acOzS6MocYVcz/KapDnod3O2XLglMHQl6Tr+rAR855SPNbQ14H3vf736PifMZbIUc5qTB8G0A1gP4kP3/rZm1iIiIOkZYUBZ2ebvININW6Nnyk0UQbxywCBZMz9w0sx7iBbdh74uoQNd0vyMHFwoiS6p5BQbYgvnlUa+Dt/1hgbDznGH80mIcfu/jqBOgmadn5uuIm7QlaVpQkbWSTUqrfRbAqwGcIiKHAGyBFQTfIiJvBXAQwO/l0joiIupoRV1GD5N1z1ZROZRJgnhvABJU8cGtZ0nP/HTMQYFLVpUCTPJ2Tffbuf2F9V8wCuxqy/yPhXtAom+A7TlRCGqPIzAY9dmOyfs+Krj1vo9N3tc6qwuu0gS1JUlaUNF5xpHBsKpeHHBXtSeBJyKilhTVI1R0TdKsB7wV1dMcN4j3C0C6errQvbgbs9Ozvo+RbilkKuz594TP6+DN242z3371rgH/YG3Vtatw6xW3Nh2L7sXdWHXtqgXbc783g1Ixkpxkrf3MwgGHUcc+Krj1vo/jpI+YtCXJ57XoqzGcgY6IiCrDpEeo6Klmsx7wVlQOZdwg3i8AmZuZm+/59PaK9izpKSwQjqqV7G5b3P02DdbirOdeNtI/4j8QtEtQH60b5zKHDTgMExbc+r2Po9JHnMfEaUvcdhedZxxZZ5iIiChLYTVHw3qEnMeG1bTNg1+t3jRBYFF1YH3rAgOYfmra93iFlUC76vGrsPYzazM7Bg6T+rNxB/EF1RUOO3lxagRvmduCTfs3heaxm6wX1R7ASjXwe+8maX+S568tq/m+ht73e21ZzTohyvB1j1LUZ8TBnmEiIipMVM9vmok4sq424Jbl7FhFlVZz2ju+cbyp57RxpIGxy8YwdulYU7WEqB7VrGcIM80LNekNdOftRvXgJrmyYDJoL+j+sNzkuKXRksh6AGMRii4/KKrFlf4dGhrSycnJwp7Pi5NuUJY46UZnEZG7VHWo7HYUKevv7PpoPXiw0opebNq/KfCSsrNOYC6jAFvmthi3w++HtogeL3cbikr1CDumwPF9Bxbmznb1dOGEZ5/QVGM2q3YGtct5L5i2v3txNy64/gKjdiV57aMeY7rNrV1b/Wsyx3jvdpIsPiOm39vsGSYiotw5AUPUVLth+YpTB+NPZRwAABnLSURBVKZ8R9QD8S6fRvUuFxGo5t3z5t6HoEkxHM6+OwGoe7KF6Sen53uVnWmAxzeOY9W1q1K33zQvNKxCg7tn20SSKwtRjzHdZtEzD7a6InunGQwTEbUBETkfwLUAugH8s6p+yHP/nwD4AwDHABwGcIWqHiiqfVF5n+5L8c76vr2BitCatibCgrBWmDo2ismAMy/nWLsDkJH+Ed9SYkHTAMc9iTANDrNMG0gyMCvqMWmC+jymSc7jRK7oQatFPx8H0BERtTgR6QZwHYBVAM4CcLGInOVZ7XsAhlT1NwB8HsBHimxjWLDhDQicQUqQgAfYPYJJB/SEDc6JGsDXCpLMGifdCw+2yTTAjiQDG+MMFEsycM1PkoFZUY8x3abfwLRFtUUYu2wscPBgHHkNLi160GoZg2QZDBMRtb5zADygqg+q6jSAmwFc4F5BVb+qqk/bf94J4IwiGxgUMITVqQ0MMuyc0qSBUVgQ1gpTx0aJqhHrx3Q2sabncR2TOCcRTgWJscvGsKi2qNBKBUkqNUQ9xrdagwADqwcWbMsJ6tfeuBbHGsesnveMAr68TuSKPkEs44SUwTARUes7HcDDrr8P2cuCvBXAuN8dIrJBRCZFZPLw4cOZNTAooHjjjjcGBj8DqwcW9A5ncVk5rFRa0SWdslYfrQf2qPeu6LX2OeA+r6CSXPOPcR0T05MIb69f40gDxxrHsPbGtZEnNiZl2KIkKZMX9ZjBdYNYuX5l83FXYO+OvYFtzCPgy+tErugTxDJOSJkzTETU+vzCH99hUyJyKYAhAL/jd7+qbgewHbCqSWTVwLh5n/XROvbu2Nu8FwKsXL8yk57DoME5RZd0ytrE5onAigXOPkTtnztfs7bU6rWd+Xlz4OZ9jGn+b9LSeFnmcicZmBX1mH2798WacjmPgC+vAXpFD/wrY6Ahg2EiotZ3CMCZrr/PAPCIdyUReS2AzQB+R1WfKaht8+IEIb55r2oHHTkqeqpnINvBQoHBlDYHjWE1eN1BZ+NIAz1LejD0jiHs270vsI2mJxFJg8Cip+eNK+5+ZRHwed83A6sHsHfH3sxP5Io+QSzjhJTBMBFR6/sOgAEReQGAHwO4CMAl7hVE5KUA/g+A81X1seKbGE/c4CLLgLLIkk5ZV68IDLLsNIio4xQUdO7bva+p9q+X6UQXQWXe4uQnmywvWtzgdmD1ACY/vrCGt1+esR+/983eHXuxcv3K0JOWJIo+QSzjhJTBMBFRi1PVYyJyJYAvwSqtdr2q3iMiHwAwqaq3AfgbACcC+L8iAgAHVfUNpTU6QpzgopXLoaVJG/ALFsJ61UyOU5qgM+gkIqrUm0mvX9Vr9MbtzQy6wmF65SPOSUsWJ4pFz0hX9PNxAB0RURtQ1d2q+iuq+iJV3WYve78dCENVX6uqz1PVs+1/lQ2EgXij/lu5HFqS4DOs9FTYYC+T45THAMKwUm+mFSSSVIGIK80AvbgD89L2dCcdsFhEmbJWxJ5hIiKqnDiXSqt+CT1Mkh7PqN7koF41k+OUJl8zqAcyi9ch70vnWVxdiNObmbanO+8Bi52GwTAREVWSaXBR9UvoYZIEn0mDf5PjlDToDAsmg57Xu17Uc+R56bzooDHtILG8ByzGVfSMcVljMExERC2tlcuhJQk+kwb/pscpSdAZFkz6Pa/femUGT0VfXUjb0+33+IHVA5jYPIGxy8bmt5f1iaJf0AugZXP2HQyGiYiopZUx+jxLcYPPpMF/nscpLJhset6gHuKSU1qSBo1xekT91g2r0BHF/b4J6plfuX5lZuXWgp5jUW1Ry6diMBgmIqKWV/To8zKlCWrzOk5hwaQ7CJRuSTT1c96SnGDEyTPOu+JJWHWJNdvXZHICFPQcQT3+ZZ/gxMFgmIiIOkKr5zW6VS34DwomB1YPNC33C4SrkNKS5AQjTp5x3jnJUT3zeT5HkNrSWurnLAqDYSIianutXIu4FQQFk0Fl1aRboHOa6qQk65ObuEFjnDzjvHOSa0traBxp+C73k+TYBfX+S5f1WrYyBsNERJSLKvXEssRU/vyCybHLxnzX1TnFlrktiZ+rCic3cfKMq1TxJOmxC+r9D0qTaBxdGJxXFSfdICKizFWt2H8r1yJuZXlM4gFUY6IVv4lAunq6MP3U9IKJO/KeNCQo8PRbnvTYBU0s4kz17VV2Hngc7BkmIqLMVa0ntko9c50kr7J3VTi58aaG1JbWMP3k9Hy6gl+Pa15XSuK8v/OYcrtVSxs6GAwTEVHmqhCsuLVyLeJWllcQWMTJjUmajzs4HOkfWZC3azIzYBbivL+zPnbOPo1vHJ/f/0W11govW6u1RETUEqrWE9vqtYhbWR5BYN4nN355tTsv32kFfEcbvu+fLE4Ak+bZm7y/57d9YAoQAK4xb1kcu2ONY/O3G0cakcerShgMExFR5qrYE1u1cmSdLs0Ay7xPbvzSfOZm5kJTINKeAKYdFBj2/vZuG4r5gLh3Rfpjl+R4VUnbBMM37TlYdhOow2T1nrvk3L5MtkNUJeyJpTBZVIPI8+TGpDfXmwNvcgJYH603pRPUltWw6tpVGFw3mGuevW+JOzsQTjMLniPJ8aqStgmGiYioWtgTS0GqNsDSK6iX18sdBEadANZH69h5+U7MzczNP6ZxpIFbr7h1wbaCniOpvHP4kxyvKmEwTERE1CaqVNs5TNUGWHr59fL68aZAhJ0ATmyeaAqEHbPTs5jYPJFrnn3eOfxJj1dVsM4wERFVWn20jpH+kQW1W6lZ1Wo7h8mr/nBWvDV1a8tq6F7c3bRO3Bz4sEB/6uBUrrWI865znMfxKhJ7homIqLKqMNNYq6h66oFbFQdYenl7edP2uoelEvT29eaaZ19EDn/Wx6tIqYJhEdkP4EkAswCOqepQFo0iIiICWivAK1vVUw/cWnGAZdoc+OFtwwtyhgGge3H3/ElAnnn2fsHqSP9IYcFxlWXRM/y7qvp4BtshIiJq0koBXtmqVts5SisFS1nwm5zCXU2iSGmuuLRSj68ppkkQEVFltVqAV6ZWSD3odFU5AUh6xSVJEN0KwXPaAXQK4MsicpeIbPBbQUQ2iMikiEwePnw45dMREVEnyXvgTzvxDmLqXdGLNdvXVC7woHjyGECa9IpLWBDtxykn5x7UufPynZUb1Jm2Z/g8VX1ERJ4L4Csi8kNVvcO9gqpuB7AdAIaGhtRvI0RERH5aMbe0TFXpeaRs5DWANOiKS21pLfRxUUG0txf46cefXpAjPTczh/GN4wCq87lOFQyr6iP2/4+JyBcAnAPgjvBHERERmWOAR50qrwGkQYP5pp+cRn20HrjtsLQlv8A9iDPZyOz07Py6ZVaJSZwmISK/JCInObcB/DcAP8iqYURERESdLK8BpIPrBnHCs09YsNyZACRIWNqS75TPIZxA2BGWbpG3NDnDzwPwTRHZC+DbAG5X1f+XTbOIiIiIOluek5M4FS28wgLtsLz0PKeNzlviNAlVfRDAygzbQkRERES2vCqE1EfrgMAqg+ARFWgHpS2FTSpiqqwqMZyOmYiIWgKnZaZOk1eFkInNE76BMASJA+2gFIqhdwxBuiXy8WVWiWGdYSIiqjxOy0ztJE7t3TwGkAamI2jyz1NY5Ze+8/oW9HB39XThhGefgMbRRmtXkyAiIioCp2WmdlGFE7vAqhAr0qUpBAXuVS+RyGCYqAXctOeg0XqXnNuXc0uIysFpmaldVOHErozZCoMC5SrMUMdgmIiIKi+oJ0u6BFu7tlaup4koSJwTu7wCxar01FahlxxgMExERC3ArycLAHTWGgXEHGJqFWETV7jlHShWYTKbKvSSA6wmQURELcA7qt5vdHqZRfuJTIVNXOEWFCg6Uxm3g6qkPzEYJiKiljC4bhCb9m/Clrkt0Dm/ulDMIabqMy2XFvRebhxptE1ZwTwnFYmDaRJERNRyTC81E1WRSYpC2CQW7VJFpYyBfH7YM0xERC3H9FIzUasKey+3yxWQvCYViYs9w0RE1HKqMhqeKC+D6wYxvnEcjSONBfe10xWQKgzkYzBMVDLTGsJE1KwKP6JEeVp17apKpBG0OwbDRERERBXEKyDFYDBMREREVFG8ApI/DqAjIiIioo7FYJiIiIiIOhaDYSIiIiLqWAyGiYjagIicLyL3i8gDInK1z/0niMjn7Pv3iEh/8a0kIlP10TpG+kewtWsrRvpH2mbWuSpiMExE1OJEpBvAdQBWATgLwMUicpZntbcCeEJVfxnARwF8uNhWEpGp+mgduzbssmagU2DqwBR2bdjFgDgnrCZB1EZMahZfcm5fYduhwpwD4AFVfRAARORmABcAuNe1zgUArrFvfx7Ax0REVFWLbCgRRZvYPNFUWxgAZp6eaZtpmKuGPcNERK3vdAAPu/4+ZC/zXUdVjwGYArDMuyER2SAikyIyefjw4ZyaS0RhgqZbbpdpmKuGwTARUesTn2XeHl+TdaCq21V1SFWHli9fnknjiCieoOmW22ka5iphMExE1PoOATjT9fcZAB4JWkdEFgHoBXC0kNYRUSzD24bRs6SnaRmnYc4Pg2Eiotb3HQADIvICEVkM4CIAt3nWuQ3Aevv2mwD8G/OFiappcN0g1mxfg94VvYAAvSt6sWb7GuYL54QD6IiIWpyqHhORKwF8CUA3gOtV9R4R+QCASVW9DcAnAdwoIg/A6hG+qLwWE1EUTsNcHAbDRERtQFV3A9jtWfZ+1+1fAPi9ottFRFR1TJMgIiIioo7FYJiIiIiIOlZLpEmYTABARMTJQoiIKC72DBMRERFRx2IwTEREREQdi8EwEREREXUsBsNERERE1LFSBcMicr6I3C8iD4jI1Vk1ioiIiIioCImDYRHpBnAdgFUAzgJwsYiclVXDiIiIiIjylqZn+BwAD6jqg6o6DeBmABdk0ywiIiIiovylqTN8OoCHXX8fAnCudyUR2QBgg/3nUyJyf4LnOgXA4wke1wq4b62rJfdvndlqkftmuJ3KWZf8dVuRdVuq7q677npcRA4keGhVPxtsVzxsVzxsVzxFtMvoeztNMCw+y3TBAtXtALaneB6IyKSqDqXZRlVx31pXO+8f940AQFWXJ3lcVY8x2xUP2xUP2xVPldqVJk3iEIAzXX+fAeCRdM0hIiIiIipOmmD4OwAGROQFIrIYwEUAbsumWURERERE+UucJqGqx0TkSgBfAtAN4HpVvSezljVLlWZRcdy31tXO+8d9ozSqeozZrnjYrnjYrngq0y5RXZDmS0RERETUETgDHRERERF1LAbDRERERNSxKhUMR03vLCIniMjn7Pv3iEh/8a1MxmDf/kRE7hWR74vIhIi0TE1T02m5ReRNIqIiUolSKiZM9k1E3my/dveIyE1FtzENg/dln4h8VUS+Z783V5fRziRE5HoReUxEfhBwv4jIP9j7/n0ReVnRbWxHpt8HBbVlv4jUReRuEZm0ly0Vka+IyD77/+cU0I4F78WgdhT5vgxo1zUi8mP7mN3t/syLyHvtdt0vIv89pzadaX/n3Gd/p260l5d6vELaVfbxepaIfFtE9trt2movf4EdJ+0TK25abC8vJI4KadcNIvKQ63idbS8v9/tYVSvxD9YgvB8BeCGAxQD2AjjLs847AXzCvn0RgM+V3e4M9+13ASyxb7+jnfbNXu8kAHcAuBPAUNntzvB1GwDwPQDPsf9+btntznj/tgN4h337LAD7y253jP37bQAvA/CDgPtXAxiHVTP9lQD2lN3mVv9n+n1QYHv2AzjFs+wjAK62b18N4MMFtGPBezGoHUW+LwPadQ2AP/VZ9yz79TwBwAvs17k7hzadCuBl9u2TAPyn/dylHq+QdpV9vATAifbtHgB77ONwC4CL7OWfcH2PFxJHhbTrBgBv8lm/1O/jKvUMm0zvfAGAHfbtzwMYFhG/yT+qJnLfVPWrqvq0/eedsOo2twLTabn/EtaX2S+KbFxKJvv2NgDXqeoTAKCqjxXcxjRM9k8BPNu+3YsWqiWuqncAOBqyygUAPq2WOwGcLCKnFtO6tmX6fVAm9+/IDgAX5v2EAe/FoHYU9r40+Iy4XQDgZlV9RlUfAvAArNc76zY9qqrftW8/CeA+WDPelnq8QtoVpKjjpar6lP1nj/1PAbwGVpwELDxeucdRIe0KUur3cZWCYb/pnb1vtPl1VPUYgCkAywppXTom++b2VlhnSK0gct9E5KUAzlTVLxbZsAyYvG6/AuBXRORbInKniJxfWOvSM9m/awBcKiKHAOwG8EfFNK0QcT+XFK1qx1QBfFlE7hKRDfay56nqo4AV4AB4bkltC2pHFY7hlfal6utdaSSFt8u+hP9SWL2KlTlennYBJR8vEekWkbsBPAbgK7B6oX9qx0ne5y4sjvK2S1Wd47XNPl4fFZETvO3yaXPuqhQMm0zvbDQFdAUZt1tELv3/27vbGKmqO47j318L8aGghOILE9OuoBEFKRYfWkGj0ZhqE5umGCWmJYa+oCW1JhqNYnzRpi+MqcY21OengrUNfXLTGLUt5UG66VrTZQEBmwBRY4u+AaIRSuDfF+eMXpfZ2bvLzNxZ5/dJJnv37Jl7/+fMzcx/zzl3LnA+cF9LI2qehm2T9BngAeDWtkXUPGVetwmkpRKXAYuAxyVNaXFczVKmfYuApyPiNNI01sr8mn4ajNf3k07WaX06PyK+DFwNLJN0aYWxlFV1Hz4EzADmAv8BfprL2xqXpEnA74BbImJ/o6p1ytoZV+X9FRGHI2IuaUb5QuDsBseuLC5Js4E7gZnABcBU4I52x1VPJ32olbm980d1JE0gTduWneKpUqlbV0u6ElgOXBsRB9sU27EaqW2TgdnAWkm7SWuBejU+LqIre04+HxGH8lTYDlJyPB6Uad8S0tozIqIPOB6Y1pboWs+3lG++jurTiHgn/3wX+AMpUdhTm37NP6ta2jRcHJX2YUTsyUnMEeAxPp7ab1tckiaSEs5nI+L3ubjy/qoXVyf0V01E7AXWkj5np+Q8aeix255HFeL6Wl5uEjnHeYoK+6uok5LhMrd37gUW5+2FwJqIGA8jOSO2LS8leISUCI+ndacN2xYR+yJiWkT0REQPaT30tRHxz2rCHZUy5+QfSRc/ImkaadnEzrZGOXZl2vcmcAWApLNJyfB7bY2ydXqB7+SrmL8C7KtNw9qYlTmn2kLS5yRNrm0DVwFb+OTnyGLg+SriaxBHpeflkHWa3yT1WS2uG/K3EZxO+qe/vwXHF/AEsC0i7i/8qdL+Gi6uDuivU2qzkZJOAK4krWf+GylPgqP7q+V51DBxbS/8QyPSOuZif1X3fjyaq+1a/SBNw75BWu+yPJf9iJQ8QfogXk1aiN4PTK865ia27S/AHmAgP3qrjrlZbRtSdy3j5NskSr5uAu4HXgc2k6/eHS+PEu07B9hIuip6ALiq6phH0bbnSNOWh0ijDkuApcDSwmu3Ird983g6Lzv5Ue+cqiiO6fm83QRsLZzfnwf+Cvw7/5zahljqnYt142jneTlMXCvzcQdJCcqphfrLc1w7gKtbFNMC0vT4YOHz8Jqq+6tBXFX31xzSNxoNkhLLewrnfz8pX1oNHJfL25JHNYhrTe6vLcAqPv7GiUrfj307ZjMzMzPrWp20TMLMzMzMrK2cDJuZmZlZ13IybGZmZmZdy8mwmZmZmXUtJ8NmZmZm1rWcDJuZmZlZ13IybC0h6YXR3JZYUo+kLSPXbD5J71dxXDMzM6vehJGrmI1eRFxTdQydQNJnI+Jw1XGYmZlZfR4ZtjGRdLukm/P2A5LW5O0rJK2StFvStDziu03SY5K2Sno535oRSfMkbZLUBywr7HuWpH5JA5IGJZ2Z97Nd0jO57LeSTizsZ52k1yS9VLjd4wxJL+byDZJm5vLTJfVJelXSj0do52WS1ubjbZf0bL6NZK2t/5K0WdKTko7L5bsl3SPpFeC6Zve9mZmZNY+TYRur9cAleft8YJKkiaRbVm4YUvdMYEVEzAL2At/K5U8BN0fEV4fUXwo8GBFz877fzuVnAY9GxBxgP/D9fMyfAwsjYh7wJPCTXP9R4Ae5/DbgF7n8QeChiLgA+G+Jtp4H3EK6NfF0YL6k44Gngesj4lzSLMv3Cs85EBELIuLXJfZvZmZmFXEybGP1GjBP0mTgINBHSlwv4ehkeFdEDBSe1yPpZGBKRKzL5SsL9fuAuyTdAXwxIj7M5W9FxMa8vYqUeJ8FzAb+LGkAuBs4TdIk4GJgdS5/BDg1P3c+8Fyd4w6nPyLejogjpPvR9+Tj7oqIN3KdZ4BLC8/5TYn9mpmZWcW8ZtjGJCIOSdoN3AT8HRgELgdmANuGVD9Y2D4MnAAIiGH2/StJ/wC+Drwk6bvAzjr1I+9n69DRZUknAXvz6HLdwzRsYOP4J+TjNvLBKPZvZmZmFfHIsB2L9aTlB+tJo8FLgYGIGDHRjIi9wD5JC3LRjbW/SZoO7IyInwG9wJz8py9IqiW9i4BXgB3AKbVySRMlzYqI/cAuSdflckn6Un7uRuCGoccdpe2kEe4z8u/fBtY1qG9mZmYdyMmwHYsNpKUHfRGxBzjA0UskGrkJWJEvoPuwUH49sCUvb5gJ/DKXbwMWSxoEppLW/f4PWAjcK2kTaRnDxbn+jcCSXL4V+EYu/yGwTNKrwMmjaXBNRBzI8a+WtBk4Ajw8ln2ZmZlZdVRiEM+scpJ6gD9FxOyKQzEzM7NPEY8Mm5mZmVnX8siwGSDpXI7+ZomDEXFRFfGYmZlZezgZNjMzM7Ou5WUSZmZmZta1nAybmZmZWddyMmxmZmZmXcvJsJmZmZl1rf8DjZpI4/Tq+DoAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 864x864 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "myShow = numerical_features_nor\n",
    "for col in myShow:\n",
    "    plt.figure(figsize=(12,12))\n",
    "    plt.subplot(2,2,1)\n",
    "    sns.distplot(trainData[col], bins=30, kde=False)\n",
    "    plt.title(\"Distributing of %s\"%col)\n",
    "    plt.subplot(2,2,2)\n",
    "    plt.scatter(range(trainData.shape[0]), trainData[col].values,color='purple')\n",
    "    plt.title(\"scatter of %s\"%col)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 删除非归一化特征"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>season</th>\n",
       "      <th>mnth</th>\n",
       "      <th>holiday</th>\n",
       "      <th>weekday</th>\n",
       "      <th>workingday</th>\n",
       "      <th>weathersit</th>\n",
       "      <th>casual</th>\n",
       "      <th>registered</th>\n",
       "      <th>cnt</th>\n",
       "      <th>dayCount</th>\n",
       "      <th>temp_nor</th>\n",
       "      <th>atemp_nor</th>\n",
       "      <th>hum_nor</th>\n",
       "      <th>windspeed_nor</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>331</td>\n",
       "      <td>654</td>\n",
       "      <td>985</td>\n",
       "      <td>0</td>\n",
       "      <td>0.360789</td>\n",
       "      <td>0.373517</td>\n",
       "      <td>0.828620</td>\n",
       "      <td>0.284606</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>131</td>\n",
       "      <td>670</td>\n",
       "      <td>801</td>\n",
       "      <td>1</td>\n",
       "      <td>0.385232</td>\n",
       "      <td>0.360541</td>\n",
       "      <td>0.715771</td>\n",
       "      <td>0.466215</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>120</td>\n",
       "      <td>1229</td>\n",
       "      <td>1349</td>\n",
       "      <td>2</td>\n",
       "      <td>0.173705</td>\n",
       "      <td>0.144830</td>\n",
       "      <td>0.449638</td>\n",
       "      <td>0.465740</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>108</td>\n",
       "      <td>1454</td>\n",
       "      <td>1562</td>\n",
       "      <td>3</td>\n",
       "      <td>0.178308</td>\n",
       "      <td>0.174649</td>\n",
       "      <td>0.607131</td>\n",
       "      <td>0.284297</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>82</td>\n",
       "      <td>1518</td>\n",
       "      <td>1600</td>\n",
       "      <td>4</td>\n",
       "      <td>0.212429</td>\n",
       "      <td>0.197158</td>\n",
       "      <td>0.449313</td>\n",
       "      <td>0.339143</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   season  mnth  holiday  weekday  workingday  weathersit  casual  registered  \\\n",
       "0       1     1        0        6           0           2     331         654   \n",
       "1       1     1        0        0           0           2     131         670   \n",
       "2       1     1        0        1           1           1     120        1229   \n",
       "3       1     1        0        2           1           1     108        1454   \n",
       "4       1     1        0        3           1           1      82        1518   \n",
       "\n",
       "    cnt  dayCount  temp_nor  atemp_nor   hum_nor  windspeed_nor  \n",
       "0   985         0  0.360789   0.373517  0.828620       0.284606  \n",
       "1   801         1  0.385232   0.360541  0.715771       0.466215  \n",
       "2  1349         2  0.173705   0.144830  0.449638       0.465740  \n",
       "3  1562         3  0.178308   0.174649  0.607131       0.284297  \n",
       "4  1600         4  0.212429   0.197158  0.449313       0.339143  "
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "trainData = trainData.drop(numerical_features,axis=1)\n",
    "testData = testData.drop(numerical_features,axis=1)\n",
    "trainData.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 热图可视化各特征相关性"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 936x648 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "data_corr = trainData.corr().abs()\n",
    "plt.figure(figsize=(13, 9))\n",
    "sns.heatmap(data_corr,annot=True)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 处理类别型特征"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "%s属性的不同取值和出现的次数'%col\n",
      "3    94\n",
      "2    92\n",
      "1    90\n",
      "4    89\n",
      "Name: season, dtype: int64\n",
      "\n",
      "%s属性的不同取值和出现的次数'%col\n",
      "12    31\n",
      "10    31\n",
      "8     31\n",
      "7     31\n",
      "5     31\n",
      "3     31\n",
      "1     31\n",
      "11    30\n",
      "9     30\n",
      "6     30\n",
      "4     30\n",
      "2     28\n",
      "Name: mnth, dtype: int64\n",
      "\n",
      "%s属性的不同取值和出现的次数'%col\n",
      "1    226\n",
      "2    124\n",
      "3     15\n",
      "Name: weathersit, dtype: int64\n",
      "\n",
      "%s属性的不同取值和出现的次数'%col\n",
      "6    53\n",
      "5    52\n",
      "4    52\n",
      "3    52\n",
      "2    52\n",
      "1    52\n",
      "0    52\n",
      "Name: weekday, dtype: int64\n"
     ]
    }
   ],
   "source": [
    "categorical_features = ['season','mnth','weathersit','weekday']\n",
    "for col in categorical_features:\n",
    "    print (\"\\n%s属性的不同取值和出现的次数'%col\")\n",
    "    print (trainData[col].value_counts())\n",
    "    trainData[col] = trainData[col].astype('object')\n",
    "    testData[col] = testData[col].astype('object')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['season_1', 'season_2', 'season_3', 'season_4', 'mnth_1', 'mnth_2',\n",
       "       'mnth_3', 'mnth_4', 'mnth_5', 'mnth_6', 'mnth_7', 'mnth_8', 'mnth_9',\n",
       "       'mnth_10', 'mnth_11', 'mnth_12', 'weathersit_1', 'weathersit_2',\n",
       "       'weathersit_3', 'weekday_0', 'weekday_1', 'weekday_2', 'weekday_3',\n",
       "       'weekday_4', 'weekday_5', 'weekday_6', 'holiday', 'workingday',\n",
       "       'casual', 'registered', 'cnt', 'dayCount', 'temp_nor', 'atemp_nor',\n",
       "       'hum_nor', 'windspeed_nor'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "categorical_features = ['season','mnth','weathersit','weekday']\n",
    "\n",
    "x_train_cat = trainData[categorical_features]\n",
    "x_train_cat = pd.get_dummies(x_train_cat)\n",
    "x_train_rest = trainData.drop(categorical_features,axis=1)\n",
    "trainData = pd.concat([x_train_cat, x_train_rest], axis = 1, ignore_index=False)\n",
    "trainData.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['season_1', 'season_2', 'season_3', 'season_4', 'mnth_1', 'mnth_2',\n",
       "       'mnth_3', 'mnth_4', 'mnth_5', 'mnth_6', 'mnth_7', 'mnth_8', 'mnth_9',\n",
       "       'mnth_10', 'mnth_11', 'mnth_12', 'weathersit_1', 'weathersit_2',\n",
       "       'weathersit_3', 'weekday_0', 'weekday_1', 'weekday_2', 'weekday_3',\n",
       "       'weekday_4', 'weekday_5', 'weekday_6', 'holiday', 'workingday',\n",
       "       'casual', 'registered', 'cnt', 'dayCount', 'temp_nor', 'atemp_nor',\n",
       "       'hum_nor', 'windspeed_nor'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "x_test_cat = testData[categorical_features]\n",
    "x_test_cat = pd.get_dummies(x_test_cat)\n",
    "x_test_rest = testData.drop(categorical_features,axis=1)\n",
    "testData = pd.concat([x_test_cat, x_test_rest], axis = 1, ignore_index=False)\n",
    "testData.columns"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 3) 岭回归"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 准备训练数据,分离特征与目标"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "# from sklearn.model_selection import train_test_split\n",
    "\n",
    "# # 随机采样20%的数据构建测试样本，其余作为训练样本\n",
    "# X_train, X_test, y_train, y_test = train_test_split(X, y, random_state=12, test_size=0.2)\n",
    "# X_train.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "365    2294\n",
       "366    1951\n",
       "367    2236\n",
       "368    2368\n",
       "369    3272\n",
       "Name: cnt, dtype: int64"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "y_train = trainData[\"cnt\"]\n",
    "X_train = trainData.drop(['cnt','casual','registered','dayCount'], axis = 1)\n",
    "\n",
    "y_test = testData[\"cnt\"]\n",
    "X_test = testData.drop(['cnt','casual','registered','dayCount'], axis = 1)\n",
    "\n",
    "y_test.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "mean y diff : 1.5914175510574313\n"
     ]
    }
   ],
   "source": [
    "# 数据标准化\n",
    "from sklearn.preprocessing import StandardScaler\n",
    "\n",
    "# 初始化对目标值的标准化器\n",
    "# 对y标准化不是必须，但对其进行标准化可以使得不同问题w的取值范围相对相同\n",
    "\n",
    "#自己实现试试...,这些参数需要保留，对测试集预测完后还需要对其进行反变换\n",
    "mean_y = y_train.mean()\n",
    "std_y = y_train.std()\n",
    "y_train = (y_train - mean_y)/std_y\n",
    "\n",
    "y_test = (y_test - mean_y)/std_y\n",
    "\n",
    "mean_test_y = y_test.mean()\n",
    "#mean_train_y = 0\n",
    "mean_diff = mean_test_y;\n",
    "\n",
    "print(\"mean y diff :\", mean_diff)\n",
    "#ss_y = StandardScaler()\n",
    "#y_train = ss_y.fit_transform(y_train.values.reshape(-1, 1))\n",
    "#y_test = ss_y.transform(y_test.reshape(-1, 1))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "最小二乘线性回归"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "RMSE on Training set : 0.39838599328198304\n",
      "RMSE on Test set : 0.7374029750237014\n",
      "r2_score on Training set : 0.8408525800280375\n",
      "r2_score on Test set : 0.6760246694654588\n"
     ]
    }
   ],
   "source": [
    "# Linear Regression\n",
    "# 1. 生成学习器实例\n",
    "lr = LinearRegression()\n",
    "\n",
    "#2. 在训练集上训练学习器\n",
    "lr.fit(X_train, y_train)\n",
    "\n",
    "#3.训练上测试，得到训练误差，实际任务中这一步不需要\n",
    "# Look at predictions on training and validation set\n",
    "mean_diff = y_test.mean()\n",
    "y_train_pred = lr.predict(X_train)\n",
    "y_test_pred = lr.predict(X_test)\n",
    "y_test_pred += mean_diff\n",
    "\n",
    "rmse_train = np.sqrt(mean_squared_error(y_train,y_train_pred))\n",
    "rmse_test = np.sqrt(mean_squared_error(y_test,y_test_pred))\n",
    "print(\"RMSE on Training set :\", rmse_train)\n",
    "print(\"RMSE on Test set :\", rmse_test)\n",
    "\n",
    "r2_score_train = r2_score(y_train,y_train_pred)\n",
    "r2_score_test = r2_score(y_test,y_test_pred)\n",
    "print(\"r2_score on Training set :\", r2_score_train)\n",
    "print(\"r2_score on Test set :\", r2_score_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Best alpha : 1.0\n",
      "cv of rmse : 0.434443098375445\n",
      "RMSE on Training set : 0.40014400069711364\n",
      "RMSE on Test set : 0.7431413836520385\n",
      "r2_score on Training set : 0.8394449017245317\n",
      "r2_score on Test set : 0.670962751932878\n"
     ]
    }
   ],
   "source": [
    "#RidgeCV缺省的score是mean squared errors \n",
    "# 1. 生成学习器实例\n",
    "# RidgeCV(alphas=(0.1, 1.0, 10.0), fit_intercept=True, normalize=False, scoring=None, cv=None, gcv_mode=None, store_cv_values=False)\n",
    "alphas = [0.01, 0.1, 1, 10, 100, 1000]\n",
    "ridge = RidgeCV(alphas = alphas,store_cv_values=True )\n",
    "\n",
    "# 2. 用训练数据度模型进行训练\n",
    "# RidgeCV采用的是广义交叉验证（Generalized Cross-Validation），留一交叉验证（N-折交叉验证）的一种有效实现方式\n",
    "ridge.fit(X_train, y_train)\n",
    "\n",
    "#通过交叉验证得到的最佳超参数alpha\n",
    "alpha = ridge.alpha_\n",
    "print(\"Best alpha :\", alpha)\n",
    "\n",
    "# 交叉验证估计的测试误差\n",
    "mse_cv = np.mean(ridge.cv_values_, axis = 0)\n",
    "rmse_cv = np.sqrt(mse_cv)\n",
    "print(\"cv of rmse :\", min(rmse_cv))\n",
    "\n",
    "#训练上测试，训练误差，实际任务中这一步不需要\n",
    "y_train_pred = ridge.predict(X_train)\n",
    "rmse_train = np.sqrt(mean_squared_error(y_train,y_train_pred))\n",
    "\n",
    "y_test_pred = ridge.predict(X_test)\n",
    "y_test_pred += mean_diff\n",
    "rmse_test = np.sqrt(mean_squared_error(y_test,y_test_pred))\n",
    "\n",
    "print(\"RMSE on Training set :\", rmse_train)\n",
    "print(\"RMSE on Test set :\", rmse_test)\n",
    "\n",
    "r2_score_train = r2_score(y_train,y_train_pred)\n",
    "r2_score_test = r2_score(y_test,y_test_pred)\n",
    "print(\"r2_score on Training set :\", r2_score_train)\n",
    "print(\"r2_score on Test set :\", r2_score_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Ridge picked 32 features and eliminated the other 0 features\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot important coefficients\n",
    "coefs = pd.Series(ridge.coef_, index = X_train.columns)\n",
    "print(\"Ridge picked \" + str(sum(coefs != 0)) + \" features and eliminated the other \" +  \\\n",
    "      str(sum(coefs == 0)) + \" features\")\n",
    "\n",
    "#正系数值最大的10个特征和负系数值最小（绝对值大）的10个特征\n",
    "imp_coefs = pd.concat([coefs.sort_values().head(10),\n",
    "                     coefs.sort_values().tail(10)])\n",
    "imp_coefs.plot(kind = \"barh\")\n",
    "plt.title(\"Coefficients in the Ridge Model\")\n",
    "plt.show()\n",
    "\n",
    "mse_mean = np.mean(ridge.cv_values_, axis = 0)\n",
    "plt.plot(np.log10(alphas), mse_mean.reshape(len(alphas),1)) \n",
    "\n",
    "plt.xlabel('log(alpha)')\n",
    "plt.ylabel('mse')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Best alpha : 0.0005827919419717718\n",
      "cv of rmse : 0.6611707751440812\n",
      "RMSE on Training set : 0.3987725617178198\n",
      "RMSE on Test set : 0.7373143756242149\n",
      "r2_score on Training set : 0.8405435771089774\n",
      "r2_score on Test set : 0.6761025164400538\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Lasso picked 27 features and eliminated the other 5 features\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 3* Lasso\n",
    "lasso = LassoCV()\n",
    "lasso.fit(X_train, y_train)\n",
    "alpha = lasso.alpha_\n",
    "print(\"Best alpha :\", alpha)    \n",
    "\n",
    "mse_cv = np.mean(lasso.mse_path_, axis = 1)\n",
    "rmse_cv = np.sqrt(mse_cv)\n",
    "print(\"cv of rmse :\", min(rmse_cv))\n",
    "\n",
    "y_train_pred = lasso.predict(X_train)\n",
    "rmse_train = np.sqrt(mean_squared_error(y_train,y_train_pred))\n",
    "print(\"RMSE on Training set :\", rmse_train)\n",
    "\n",
    "\n",
    "y_test_pred = lasso.predict(X_test)\n",
    "y_test_pred += mean_diff\n",
    "\n",
    "rmse_test = np.sqrt(mean_squared_error(y_test,y_test_pred))\n",
    "print(\"RMSE on Test set :\", rmse_test)\n",
    "\n",
    "r2_score_train = r2_score(y_train,y_train_pred)\n",
    "r2_score_test = r2_score(y_test,y_test_pred)\n",
    "print(\"r2_score on Training set :\", r2_score_train)\n",
    "print(\"r2_score on Test set :\", r2_score_test)\n",
    "\n",
    "# Plot important coefficients\n",
    "mses = np.mean(lasso.mse_path_, axis = 1)\n",
    "plt.plot(np.log10(lasso.alphas_), mses) \n",
    "#plt.plot(np.log10(lasso.alphas_)*np.ones(3), [0.3, 0.4, 1.0])\n",
    "plt.xlabel('log(alpha)')\n",
    "plt.ylabel('mse')\n",
    "plt.show()\n",
    "\n",
    "coefs = pd.Series(lasso.coef_, index = X_train.columns)\n",
    "print(\"Lasso picked \" + str(sum(coefs != 0)) + \" features and eliminated the other \" +  \\\n",
    "      str(sum(coefs == 0)) + \" features\")\n",
    "imp_coefs = pd.concat([coefs.sort_values().head(10),\n",
    "                     coefs.sort_values().tail(10)])\n",
    "imp_coefs.plot(kind = \"barh\")\n",
    "plt.title(\"Coefficients in the Lasso Model\")\n",
    "plt.show()\n",
    "\n",
    "mses = np.mean(lasso.mse_path_, axis = 1)\n",
    "plt.plot(np.log10(lasso.alphas_), mses) \n",
    "#plt.plot(np.log10(lasso.alphas_)*np.ones(3), [0.3, 0.4, 1.0])\n",
    "plt.xlabel('log(alpha)')\n",
    "plt.ylabel('mse')\n",
    "plt.show() "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 对测试集进行测试，生成提交文件"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "y_test_pred = lasso.predict(X_test)\n",
    "y_test_pred += mean_diff\n",
    "y_test_pred = y_test_pred * std_y +  mean_y\n",
    "\n",
    "#生成提交测试结果\n",
    "df = pd.DataFrame({'instant':np.arange(len(y_test_pred))+1,'cnt':y_test_pred})\n",
    "#df.reindex(columns=['instant'])\n",
    "#y = pd.Series(data = y_test_pred, name = 'cnt')\n",
    "#df = pd.concat([testID, y], axis = 1, ignore_index=True)\n",
    "df.to_csv('submission.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 366 entries, 0 to 365\n",
      "Data columns (total 2 columns):\n",
      "instant    366 non-null int32\n",
      "cnt        366 non-null float64\n",
      "dtypes: float64(1), int32(1)\n",
      "memory usage: 4.4 KB\n"
     ]
    }
   ],
   "source": [
    "df.info()"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
